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android / platform / external / ARMComputeLibrary / upstream-master / . / src / core / CL / cl_kernels / common / gemm.cl
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/*
* Copyright (c) 2017-2022 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "gemm_helpers.h"
#include "repeat.h"
#if defined(M0) && defined(N0) && defined(K0) && defined(H0) && defined(DATA_TYPE)
#define CONCAT(a, b) a##b
#define ARM_DOT1(a, b, c) \
({ \
c = fma(a, b, c); \
})
#define ARM_DOT2(a, b, c) \
({ \
c = fma(a.s0, b.s0, c); \
c = fma(a.s1, b.s1, c); \
})
#define ARM_DOT3(a, b, c) \
({ \
ARM_DOT2(a, b, c); \
c = fma((a.s2), (b.s2), c); \
})
#define ARM_DOT4(a, b, c) \
({ \
ARM_DOT3(a, b, c); \
c = fma((a.s3), (b.s3), c); \
})
#define ARM_DOT8(a, b, c) \
({ \
ARM_DOT4((a.lo), (b.lo), c); \
ARM_DOT4((a.hi), (b.hi), c); \
})
#define ARM_DOT16(a, b, c) \
({ \
ARM_DOT8((a.lo), (b.lo), c); \
ARM_DOT8((a.hi), (b.hi), c); \
})
#if N0 == 2
#define ARM_DOT_K0XN0(k0, a, b, c) \
({ \
CONCAT(ARM_DOT, k0) \
((a), (b##0), (c.s0)); \
CONCAT(ARM_DOT, k0) \
((a), (b##1), (c.s1)); \
})
#elif N0 == 3 // N0 == 3
#define ARM_DOT_K0XN0(k0, a, b, c) \
({ \
CONCAT(ARM_DOT, k0) \
((a), (b##0), (c.s0)); \
CONCAT(ARM_DOT, k0) \
((a), (b##1), (c.s1)); \
CONCAT(ARM_DOT, k0) \
((a), (b##2), (c.s2)); \
})
#elif N0 == 4 // N0 == 4
#define ARM_DOT_K0XN0(k0, a, b, c) \
({ \
CONCAT(ARM_DOT, k0) \
((a), (b##0), (c.s0)); \
CONCAT(ARM_DOT, k0) \
((a), (b##1), (c.s1)); \
CONCAT(ARM_DOT, k0) \
((a), (b##2), (c.s2)); \
CONCAT(ARM_DOT, k0) \
((a), (b##3), (c.s3)); \
})
#elif N0 == 8 // N0 == 8
#define ARM_DOT_K0XN0(k0, a, b, c) \
({ \
CONCAT(ARM_DOT, k0) \
((a), (b##0), (c.s0)); \
CONCAT(ARM_DOT, k0) \
((a), (b##1), (c.s1)); \
CONCAT(ARM_DOT, k0) \
((a), (b##2), (c.s2)); \
CONCAT(ARM_DOT, k0) \
((a), (b##3), (c.s3)); \
CONCAT(ARM_DOT, k0) \
((a), (b##4), (c.s4)); \
CONCAT(ARM_DOT, k0) \
((a), (b##5), (c.s5)); \
CONCAT(ARM_DOT, k0) \
((a), (b##6), (c.s6)); \
CONCAT(ARM_DOT, k0) \
((a), (b##7), (c.s7)); \
})
#elif N0 == 16 // N0 == 16
#define ARM_DOT_K0XN0(k0, a, b, c) \
({ \
CONCAT(ARM_DOT, k0) \
((a), (b##0), (c.s0)); \
CONCAT(ARM_DOT, k0) \
((a), (b##1), (c.s1)); \
CONCAT(ARM_DOT, k0) \
((a), (b##2), (c.s2)); \
CONCAT(ARM_DOT, k0) \
((a), (b##3), (c.s3)); \
CONCAT(ARM_DOT, k0) \
((a), (b##4), (c.s4)); \
CONCAT(ARM_DOT, k0) \
((a), (b##5), (c.s5)); \
CONCAT(ARM_DOT, k0) \
((a), (b##6), (c.s6)); \
CONCAT(ARM_DOT, k0) \
((a), (b##7), (c.s7)); \
CONCAT(ARM_DOT, k0) \
((a), (b##8), (c.s8)); \
CONCAT(ARM_DOT, k0) \
((a), (b##9), (c.s9)); \
CONCAT(ARM_DOT, k0) \
((a), (b##A), (c.sA)); \
CONCAT(ARM_DOT, k0) \
((a), (b##B), (c.sB)); \
CONCAT(ARM_DOT, k0) \
((a), (b##C), (c.sC)); \
CONCAT(ARM_DOT, k0) \
((a), (b##D), (c.sD)); \
CONCAT(ARM_DOT, k0) \
((a), (b##E), (c.sE)); \
CONCAT(ARM_DOT, k0) \
((a), (b##F), (c.sF)); \
})
#else // N0 not supported
#error "N0 value not supported"
#endif // N0 conditions
#if defined(GEMM_MM_RESHAPED_ONLY_RHS_T)
/** This OpenCL kernel computes the matrix multiplication between 2 matrices.
* The LHS matrix is NOT reshaped
* The RHS is reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the block K0xN0 is transposed
* @note This kernel is duplicated in /experimental/gemm_fused_post_ops/act_eltwise_op_act/gemm_mm_reshaped_only_rhs.cl
*
* @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time.
* @note The GEMM's dimensions (M,N and K) must be passed at runtime as kernel parameters.
* @note The block's dimensions used for reshaping the RHS matrix (N0 and K0) must be passed at compile time using -DN0 and -DK0 (e.g. -DN0=8, -DK0=4).
* @note The number of M0 rows to process must be passed at compile time using -DM0 (e.g. -DM0=2)
* @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2)
* @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time.
* @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1)
* @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1)
* @note Only the following configurations of M0, N0 and K0 are currently supported:
* - M0 = 1, 2, 3, 4, 5, 6, 7, 8
* - N0 = 2, 3, 4, 8, 16
* - K0 = 2, 3, 4, 8, 16
* - H0 >= 1
*
* @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
* The activation function is performed after the bias addition
* @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time:
* -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
* -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor.
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix
*
* @param[in] lhs_ptr Pointer to the LHS matrix. Supported data type: F16/F32
* @param[in] lhs_stride_x Stride of the LHS matrix in X dimension (in bytes)
* @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] lhs_stride_y Stride of the LHS matrix in Y dimension (in bytes)
* @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS matrix
* @param[in] rhs_ptr Pointer to the RHS reshaped matrix. Supported data type: same as @p lhs_ptr
* @param[in] rhs_stride_x Stride of the RHS reshaped matrix in X dimension (in bytes)
* @param[in] rhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] rhs_stride_y Stride of the RHS reshaped matrix in Y dimension (in bytes)
* @param[in] rhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS reshaped matrix
* @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
* @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
* @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] bias_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
* @param[in] bias_step_y (Optional) bias_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes)
* @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
* @param[in] lhs_stride_z Stride of the LHS matrix in Z dimension (in bytes)
* @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes)
* @param[in] bias_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] lhs_cross_plane_pad (Optional) Bottom paddings for LHS matrix in unit of elements (only if defined REINTERPRET_INPUT_AS_3D)
* @param[in] dst_cross_plane_pad (Optional) Bottom paddings for the output matrix in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
* @param[in] M Number of rows in LHS matrix not reshaped.
* @param[in] N Number of columns in RHS matrix not reshaped.
* @param[in] K Number of columns in LHS matrix and rows in RHS matrix not reshaped.
*/
__kernel void gemm_mm_reshaped_only_rhs_t(IMAGE_DECLARATION(lhs),
IMAGE_DECLARATION(rhs),
#if defined(BETA)
IMAGE_DECLARATION(bias),
#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint lhs_stride_z,
uint rhs_stride_z,
#if defined(BETA)
uint bias_stride_z,
#endif //defined(BETA)
uint dst_stride_z
#if defined(REINTERPRET_INPUT_AS_3D)
,
uint lhs_cross_plane_pad
#endif // REINTERPRET_INPUT_AS_3D
#if defined(REINTERPRET_OUTPUT_AS_3D)
,
uint dst_cross_plane_pad
#endif // REINTERPRET_OUTPUT_AS_3D
,
const int M,
const int N,
const int K)
{
// Block size
#define RHS_BLOCK_SIZE ((K0) * (N0))
// RHS offset and step X
#if defined(RHS_INTERLEAVE)
#define RHS_OFFSET_X (K0)
#define RHS_STEP_X ((K0) * (H0))
#define RHS_STEP_LOOP (1)
#else // defined(RHS_INTERLEAVE)
#define RHS_OFFSET_X (RHS_BLOCK_SIZE)
#define RHS_STEP_X (K0)
#define RHS_STEP_LOOP (H0)
#endif // defined(RHS_INTERLEAVE)
uint x = get_global_id(0);
uint y = get_global_id(1);
uint z = get_global_id(2);
const bool cond_y = y == 0;
const bool cond_x = ((x + 1) * N0 >= N);
#if defined(DUMMY_WORK_ITEMS)
if((x * N0 >= N) || (y * M0 >= M))
{
return;
}
#endif // defined(DUMMY_WORK_ITEMS)
// Compute LHS matrix address
uint lhs_offset = lhs_offset_first_element_in_bytes + COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * (uint)lhs_stride_y;
// Compute RHS reshaped matrix address
uint rhs_offset = rhs_offset_first_element_in_bytes + (x % H0) * (uint)RHS_OFFSET_X * sizeof(DATA_TYPE) + (x / (uint)H0) * rhs_stride_y;
#if defined(MATRIX_B_DEPTH)
// Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
rhs_offset += (z % MATRIX_B_DEPTH) * rhs_stride_z;
#else // defined(MATRIX_B_DEPTH)
rhs_offset += z * rhs_stride_z;
#endif // defined(MATRIX_B_DEPTH)
REPEAT_VAR_INIT_TO_CONST(8, uint, zlhs, 0); //uint zlhs0=0,zlhs1=0,zlhs2=0,... zlhs7=0;
REPEAT_VAR_INIT_TO_CONST(16, uint, zero, 0);
#if defined(REINTERPRET_INPUT_AS_3D)
// The plane (zlhs) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
CALCULATE_Z_OFFSET(M0, uint, zlhs, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply lhs_stride_z by DEPTH_GEMM3D
lhs_offset += z * lhs_stride_z * DEPTH_GEMM3D;
#else // defined(REINTERPRET_INPUT_AS_3D)
// Add offset for batched GEMM
lhs_offset += z * lhs_stride_z;
#endif // defined(REINTERPRET_INPUT_AS_3D)
// Initialize the accumulators
REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE, N0), c, 0); //VEC_DATA_TYPE(DATA_TYPE, N0) c0=0,c1=0,c2=0,... c(M0-1)=0;
int i = 0;
for(; i <= (K - K0); i += K0)
{
// Supported cases (M0, K0):
// 1,2 - 1,3 - 1,4 - 1,8 - 1,16
// 2,2 - 2,3 - 2,4 - 2,8 - 2,16
// 3,2 - 3,3 - 3,4 - 3,8 - 3,16
// 4,2 - 4,3 - 4,4 - 4,8 - 4,16
// 5,2 - 5,3 - 5,4 - 5,8 - 5,16
// 6,2 - 6,3 - 6,4 - 6,8 - 6,16
// 7,2 - 7,3 - 7,4 - 7,8 - 7,16
// 8,2 - 8,3 - 8,4 - 8,8 - 8,16
// Load values from LHS matrix
LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zlhs);
// Load values from RHS reshaped matrix
LOAD_BLOCK(N0, K0, DATA_TYPE, b, rhs_ptr, rhs_offset, RHS_STEP_X * sizeof(DATA_TYPE), zero);
// Accumulate
ARM_DOT_K0XN0(K0, a0, b, c0);
#if M0 > 1
ARM_DOT_K0XN0(K0, a1, b, c1);
#endif // M0 > 1
#if M0 > 2
ARM_DOT_K0XN0(K0, a2, b, c2);
#endif // M0 > 2
#if M0 > 3
ARM_DOT_K0XN0(K0, a3, b, c3);
#endif // M0 > 3
#if M0 > 4
ARM_DOT_K0XN0(K0, a4, b, c4);
#endif // M0 > 4
#if M0 > 5
ARM_DOT_K0XN0(K0, a5, b, c5);
#endif // M0 > 5
#if M0 > 6
ARM_DOT_K0XN0(K0, a6, b, c6);
#endif // M0 > 6
#if M0 > 7
ARM_DOT_K0XN0(K0, a7, b, c7);
#endif // M0 > 7
lhs_offset += K0 * sizeof(DATA_TYPE);
rhs_offset += (N0 * RHS_STEP_X * RHS_STEP_LOOP) * sizeof(DATA_TYPE);
}
// Left-over accumulations
for(; i < K; ++i)
{
// Load values from LHS matrix
LOAD_BLOCK(M0, 1, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zlhs);
// Load values from RHS reshaped matrix
LOAD_BLOCK(N0, 1, DATA_TYPE, b, rhs_ptr, rhs_offset, RHS_STEP_X * sizeof(DATA_TYPE), zero);
// Accumulate
ARM_DOT_K0XN0(1, a0, b, c0);
#if M0 > 1
ARM_DOT_K0XN0(1, a1, b, c1);
#endif // M0 > 1
#if M0 > 2
ARM_DOT_K0XN0(1, a2, b, c2);
#endif // M0 > 2
#if M0 > 3
ARM_DOT_K0XN0(1, a3, b, c3);
#endif // M0 > 3
#if M0 > 4
ARM_DOT_K0XN0(1, a4, b, c4);
#endif // M0 > 4
#if M0 > 5
ARM_DOT_K0XN0(1, a5, b, c5);
#endif // M0 > 5
#if M0 > 6
ARM_DOT_K0XN0(1, a6, b, c6);
#endif // M0 > 6
#if M0 > 7
ARM_DOT_K0XN0(1, a7, b, c7);
#endif // M0 > 7
lhs_offset += sizeof(DATA_TYPE);
rhs_offset += sizeof(DATA_TYPE);
}
__global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * dst_stride_y);
REPEAT_VAR_INIT_TO_CONST(8, uint, zout, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0;
#if defined(REINTERPRET_OUTPUT_AS_3D)
// The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += z * dst_stride_z;
#endif // defined(REINTERPRET_OUTPUT_AS_3D)
// Multiply by the weight of matrix-matrix product and store the result
#if defined(ALPHA)
SCALE_BLOCK(M0, DATA_TYPE, c, ALPHA);
#endif // defined(ALPHA)
// Add beta*bias
#if defined(BETA)
#if defined(BROADCAST_BIAS)
__global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE));
LOAD_BLOCK_BOUNDARY_AWARE(1, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, 1, PARTIAL_STORE_N0, false, cond_x);
#ifndef UNIT_BETA
SCALE_BLOCK(1, DATA_TYPE, bias, BETA);
#endif // UNIT_BIAS
// c = c + bias[broadcasted]
ADD_BLOCK_BROADCAST(M0, c, bias0);
#else // defined(BROADCAST_BIAS)
__global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * bias_stride_y) + z * bias_stride_z;
LOAD_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#ifndef UNIT_BETA
SCALE_BLOCK(M0, DATA_TYPE, bias, BETA);
#endif // UNIT_BIAS
// c = c + bias
ADD_BLOCK(M0, c, bias);
#endif // defined(BROADCAST_BIAS)
#endif // defined(BETA)
#if defined(ACTIVATION_TYPE)
ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE, VEC_SIZE, c, A_VAL, B_VAL);
#endif // defined(ACTIVATION_TYPE)
// Store output block
STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#undef RHS_BLOCK_SIZE
#undef RHS_OFFSET_X
#undef RHS_STEP_X
#undef RHS_STEP_LOOP
}
#endif // defined(GEMM_MM_RESHAPED_ONLY_RHS_T)
#if defined(OPENCL_IMAGE_SUPPORT) && defined(GEMM_MM_RESHAPED_ONLY_RHS_T_TEXTURE)
/** This OpenCL kernel computes the matrix multiplication between 2 matrices. The RHS matrix is stored in OpenCL image
* The LHS matrix is NOT reshaped
* The RHS is reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the block K0xN0 is transposed
* @note This kernel is duplicated in /experimental/gemm_fused_post_ops/act_eltwise_op_act/gemm_mm_reshaped_only_rhs.cl
*
* @note -DOPENCL_IMAGE_SUPPORT must be passed at compile time in order to compile this OpenCL kernel
* @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time.
* @note The GEMM's dimensions (M,N and K) must be passed at runtime as kernel parameters.
* @note The height of the RHS matrix, defined before creating the OpenCL image object from the OpenCL buffer, should be passed at compile time using -DRHS_HEIGHT=<value> (e.g. -DRHS_HEIGHT=32)
* Since we cannot create a 3d image from a buffer, the third dimension could be collapsed with the second dimension so RHS_HEIGHT
* could be different from the value returned by get_image_height(rhs_img).
* @note The block's dimensions used for reshaping the RHS matrix (N0 and K0) must be passed at compile time using -DN0 and -DK0 (e.g. -DN0=8, -DK0=4).
* @note The number of M0 rows to process must be passed at compile time using -DM0 (e.g. -DM0=2)
* @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2)
* @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time.
* @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1)
* @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1)
* @note Only the following configurations of M0, N0 and K0 are currently supported:
* - M0 = 1, 2, 3, 4, 5, 6, 7, 8
* - N0 = 4, 8, 16
* - K0 = 4, 8, 16
* - H0 >= 1
*
* @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
* The activation function is performed after the bias addition
* @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time:
* -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
* -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor.
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix
*
* @param[in] lhs_ptr Pointer to the LHS matrix. Supported data type: F32
* @param[in] lhs_stride_x Stride of the LHS matrix in X dimension (in bytes)
* @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] lhs_stride_y Stride of the LHS matrix in Y dimension (in bytes)
* @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS matrix
* @param[in] rhs_img The RHS reshaped matrix as OpenCL image object. Supported data type: same as @p lhs_ptr
* @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
* @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
* @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] bias_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
* @param[in] bias_step_y (Optional) bias_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes)
* @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
* @param[in] lhs_stride_z Stride of the LHS matrix in Z dimension (in bytes)
* @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes)
* @param[in] bias_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] lhs_cross_plane_pad (Optional) Bottom paddings for LHS matrix in unit of elements (only if defined REINTERPRET_INPUT_AS_3D)
* @param[in] dst_cross_plane_pad (Optional) Bottom paddings for the output matrix in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
* @param[in] M Number of rows in LHS matrix not reshaped.
* @param[in] N Number of columns in RHS matrix not reshaped.
* @param[in] K Number of columns in LHS matrix and rows in RHS matrix not reshaped.
*/
__kernel void gemm_mm_reshaped_only_rhs_t_texture(IMAGE_DECLARATION(lhs),
__read_only image2d_t rhs_img,
#if defined(BETA)
IMAGE_DECLARATION(bias),
#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint lhs_stride_z,
uint rhs_stride_z,
#if defined(BETA)
uint bias_stride_z,
#endif //defined(BETA)
uint dst_stride_z
#if defined(REINTERPRET_INPUT_AS_3D)
,
uint lhs_cross_plane_pad
#endif // REINTERPRET_INPUT_AS_3D
#if defined(REINTERPRET_OUTPUT_AS_3D)
,
uint dst_cross_plane_pad
#endif // REINTERPRET_OUTPUT_AS_3D
,
const int M,
const int N,
const int K)
{
// Pixel unit
#define PIXEL_UNIT CONVERT_VECTOR_SIZE_TO_PIXEL_UNIT(K0)
const uint LEFTOVER_K = K % K0;
// Block size
#define RHS_BLOCK_SIZE (PIXEL_UNIT * (N0))
// RHS offset and step X
#if defined(RHS_INTERLEAVE)
#define RHS_OFFSET_X (PIXEL_UNIT)
#define RHS_STEP_X (PIXEL_UNIT * (H0))
#define RHS_STEP_LOOP (1)
#else // defined(RHS_INTERLEAVE)
#define RHS_OFFSET_X (RHS_BLOCK_SIZE)
#define RHS_STEP_X PIXEL_UNIT
#define RHS_STEP_LOOP (H0)
#endif // defined(RHS_INTERLEAVE)
uint x = get_global_id(0);
uint y = get_global_id(1);
uint z = get_global_id(2);
const bool cond_y = y == 0;
const bool cond_x = ((x + 1) * N0 >= N);
#if defined(DUMMY_WORK_ITEMS)
if((x * N0 >= N) || (y * M0 >= M))
{
return;
}
#endif // defined(DUMMY_WORK_ITEMS)
// Compute LHS matrix address
uint lhs_offset = lhs_offset_first_element_in_bytes + COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * (uint)lhs_stride_y;
#if defined(MATRIX_B_DEPTH)
// Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
const uint z_rhs = (get_global_id(2) % MATRIX_B_DEPTH);
#else // defined(MATRIX_B_DEPTH)
const uint z_rhs = get_global_id(2);
#endif // defined(MATRIX_B_DEPTH)
// Compute RHS matrix coordinates
uint x_rhs = (get_global_id(0) % H0) * (uint)RHS_OFFSET_X;
const uint y_rhs = (get_global_id(0) / (uint)H0) + z_rhs * RHS_HEIGHT;
REPEAT_VAR_INIT_TO_CONST(M0, uint, zlhs, 0);
REPEAT_VAR_INIT_TO_CONST(16, uint, zero, 0);
#if defined(REINTERPRET_INPUT_AS_3D)
// The plane (zlhs) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
CALCULATE_Z_OFFSET(M0, uint, zlhs, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply lhs_stride_z by DEPTH_GEMM3D
lhs_offset += z * lhs_stride_z * DEPTH_GEMM3D;
#else // defined(REINTERPRET_INPUT_AS_3D)
// Add offset for batched GEMM
lhs_offset += z * lhs_stride_z;
#endif // defined(REINTERPRET_INPUT_AS_3D)
// Initialize the accumulators
REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE, N0), c, 0);
int i = 0;
for(; i <= (K - K0); i += K0)
{
// Load values from LHS matrix
LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zlhs);
// Load values from RHS matrix stored in a cl_image
REPEAT_VAR_INIT_TO_CONST(N0, VEC_DATA_TYPE(DATA_TYPE, K0), b, 0);
LOAD_TEXTURE2D(N0, PIXEL_UNIT, DATA_TYPE, b, rhs_img, x_rhs, y_rhs, RHS_STEP_X, 0);
// Accumulate
ARM_DOT_K0XN0(K0, a0, b, c0);
#if M0 > 1
ARM_DOT_K0XN0(K0, a1, b, c1);
#endif // M0 > 1
#if M0 > 2
ARM_DOT_K0XN0(K0, a2, b, c2);
#endif // M0 > 2
#if M0 > 3
ARM_DOT_K0XN0(K0, a3, b, c3);
#endif // M0 > 3
#if M0 > 4
ARM_DOT_K0XN0(K0, a4, b, c4);
#endif // M0 > 4
#if M0 > 5
ARM_DOT_K0XN0(K0, a5, b, c5);
#endif // M0 > 5
#if M0 > 6
ARM_DOT_K0XN0(K0, a6, b, c6);
#endif // M0 > 6
#if M0 > 7
ARM_DOT_K0XN0(K0, a7, b, c7);
#endif // M0 > 7
lhs_offset += K0 * sizeof(DATA_TYPE);
x_rhs += N0 * RHS_STEP_X * RHS_STEP_LOOP;
}
if(LEFTOVER_K != 0)
{
// Note: We cannot read out-of-bound elements from the RHS matrix because
// the RHS width is always multiple of K0. This is not be true for the LHS matrix
// Left-over accumulations for LHS matrix
union UNION_VEC_TYPE
{
DATA_TYPE s[K0];
VEC_DATA_TYPE(DATA_TYPE, K0)
v;
};
union UNION_VEC_TYPE a0 = {.v = 0 };
#if M0 > 1
union UNION_VEC_TYPE a1 = {.v = 0 };
#endif // M0 > 1
#if M0 > 2
union UNION_VEC_TYPE a2 = {.v = 0 };
#endif // M0 > 2
#if M0 > 3
union UNION_VEC_TYPE a3 = {.v = 0 };
#endif // M0 > 3
#if M0 > 4
union UNION_VEC_TYPE a4 = {.v = 0 };
#endif // M0 > 4
#if M0 > 5
union UNION_VEC_TYPE a5 = {.v = 0 };
#endif // M0 > 5
#if M0 > 6
union UNION_VEC_TYPE a6 = {.v = 0 };
#endif // M0 > 6
#if M0 > 7
union UNION_VEC_TYPE a7 = {.v = 0 };
#endif // M0 > 7
REPEAT_VAR_INIT_TO_CONST(N0, VEC_DATA_TYPE(DATA_TYPE, K0), b, 0);
// Load from RHS matrix
LOAD_TEXTURE2D(N0, PIXEL_UNIT, DATA_TYPE, b, rhs_img, x_rhs, y_rhs, RHS_STEP_X, 0);
// Load from LHS matrix
for(int k = 0; k < LEFTOVER_K; ++k)
{
a0.s[k] = *(__global DATA_TYPE *)(lhs_ptr + lhs_offset + 0 * lhs_stride_y + zlhs0);
#if M0 > 1
a1.s[k] = *(__global DATA_TYPE *)(lhs_ptr + lhs_offset + 1 * lhs_stride_y + zlhs1);
#endif // M0 > 1
#if M0 > 2
a2.s[k] = *(__global DATA_TYPE *)(lhs_ptr + lhs_offset + 2 * lhs_stride_y + zlhs2);
#endif // M0 > 2
#if M0 > 3
a3.s[k] = *(__global DATA_TYPE *)(lhs_ptr + lhs_offset + 3 * lhs_stride_y + zlhs3);
#endif // M0 > 3
#if M0 > 4
a4.s[k] = *(__global DATA_TYPE *)(lhs_ptr + lhs_offset + 4 * lhs_stride_y + zlhs4);
#endif // M0 > 4
#if M0 > 5
a5.s[k] = *(__global DATA_TYPE *)(lhs_ptr + lhs_offset + 5 * lhs_stride_y + zlhs5);
#endif // M0 > 5
#if M0 > 6
a6.s[k] = *(__global DATA_TYPE *)(lhs_ptr + lhs_offset + 6 * lhs_stride_y + zlhs6);
#endif // M0 > 6
#if M0 > 7
a7.s[k] = *(__global DATA_TYPE *)(lhs_ptr + lhs_offset + 7 * lhs_stride_y + zlhs7);
#endif // M0 > 7
lhs_offset += sizeof(DATA_TYPE);
}
// Accumulate
ARM_DOT_K0XN0(K0, a0.v, b, c0);
#if M0 > 1
ARM_DOT_K0XN0(K0, a1.v, b, c1);
#endif // M0 > 1
#if M0 > 2
ARM_DOT_K0XN0(K0, a2.v, b, c2);
#endif // M0 > 2
#if M0 > 3
ARM_DOT_K0XN0(K0, a3.v, b, c3);
#endif // M0 > 3
#if M0 > 4
ARM_DOT_K0XN0(K0, a4.v, b, c4);
#endif // M0 > 4
#if M0 > 5
ARM_DOT_K0XN0(K0, a5.v, b, c5);
#endif // M0 > 5
#if M0 > 6
ARM_DOT_K0XN0(K0, a6.v, b, c6);
#endif // M0 > 6
#if M0 > 7
ARM_DOT_K0XN0(K0, a7.v, b, c7);
#endif // M0 > 7
}
__global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * dst_stride_y);
REPEAT_VAR_INIT_TO_CONST(M0, uint, zout, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0;
#if defined(REINTERPRET_OUTPUT_AS_3D)
// The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += z * dst_stride_z;
#endif // defined(REINTERPRET_OUTPUT_AS_3D)
// Multiply by the weight of matrix-matrix product and store the result
#if defined(ALPHA)
SCALE_BLOCK(M0, DATA_TYPE, c, ALPHA);
#endif // defined(ALPHA)
// Add beta*bias
#if defined(BETA)
#if defined(BROADCAST_BIAS)
__global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE));
LOAD_BLOCK_BOUNDARY_AWARE(1, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, 1, PARTIAL_STORE_N0, false, cond_x);
#ifndef UNIT_BETA
SCALE_BLOCK(1, DATA_TYPE, bias, BETA);
#endif // UNIT_BIAS
// c = c + bias[broadcasted]
ADD_BLOCK_BROADCAST(M0, c, bias0);
#else // defined(BROADCAST_BIAS)
__global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * bias_stride_y) + z * bias_stride_z;
LOAD_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#ifndef UNIT_BETA
SCALE_BLOCK(M0, DATA_TYPE, bias, BETA);
#endif // UNIT_BIAS
// c = c + bias
ADD_BLOCK(M0, c, bias);
#endif // defined(BROADCAST_BIAS)
#endif // defined(BETA)
#if defined(ACTIVATION_TYPE)
ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE, VEC_SIZE, c, A_VAL, B_VAL);
#endif // defined(ACTIVATION_TYPE)
// Store output block
STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#undef RHS_BLOCK_SIZE
#undef RHS_OFFSET_X
#undef RHS_STEP_X
#undef RHS_STEP_LOOP
#undef PIXEL_UNIT
}
#endif // defined(OPENCL_IMAGE_SUPPORT) && defined(GEMM_MM_RESHAPED_ONLY_RHS_T_TEXTURE)
#define VFMA(a, b, c) \
({ \
c = fma(a, b, c); \
})
#if M0 == 1
#define VFMA_M0xN0(i, a, b, c) \
({ \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \
})
#elif M0 == 2 // M0 == 2
#define VFMA_M0xN0(i, a, b, c) \
({ \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \
})
#elif M0 == 3 // M0 == 3
#define VFMA_M0xN0(i, a, b, c) \
({ \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \
})
#elif M0 == 4 // M0 == 4
#define VFMA_M0xN0(i, a, b, c) \
({ \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \
})
#elif M0 == 5 // M0 == 5
#define VFMA_M0xN0(i, a, b, c) \
({ \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \
})
#elif M0 == 6 // M0 == 6
#define VFMA_M0xN0(i, a, b, c) \
({ \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##5).s##i), b, (c##5)); \
})
#elif M0 == 7 // M0 == 7
#define VFMA_M0xN0(i, a, b, c) \
({ \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##5).s##i), b, (c##5)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##6).s##i), b, (c##6)); \
})
#elif M0 == 8 // M0 == 8
#define VFMA_M0xN0(i, a, b, c) \
({ \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##5).s##i), b, (c##5)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##6).s##i), b, (c##6)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##7).s##i), b, (c##7)); \
})
#else // M0 not supported
#error "M0 not supported"
#endif // M0 not supported
#if defined(GEMM_MM_RESHAPED_ONLY_RHS_NT)
/** This OpenCL kernel computes the matrix multiplication between 2 matrices.
* The LHS matrix is NOT reshaped
* The RHS is reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the block K0xN0 is NOT transposed
* @note This kernel is duplicated in /experimental/gemm_fused_post_ops/act_eltwise_op_act/gemm_mm_reshaped_only_rhs.cl
*
* @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time.
* @note The GEMM's dimensions (M,N and K) must be passed at runtime as kernel parameters.
* @note The block's dimensions used for reshaping the RHS matrix (N0 and K0) must be passed at compile time using -DN0 and -DK0 (e.g. -DN0=8, -DK0=4).
* @note The number of M0 rows to process must be passed at compile time using -DM0 (e.g. -DM0=2)
* @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2)
* @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time.
* @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1)
* @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1)
* @note Only the following configurations of M0, N0 and K0 are currently supported:
* - M0 = 1, 2, 3, 4, 5, 6, 7, 8
* - N0 = 2, 3, 4, 8, 16
* - K0 = 2, 3, 4, 8, 16
* - H0 >= 1
*
* @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
* The activation function is performed after the bias addition
* @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time:
* -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
* -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor.
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix
*
* @param[in] lhs_ptr Pointer to the LHS matrix. Supported data type: F16/F32
* @param[in] lhs_stride_x Stride of the LHS matrix in X dimension (in bytes)
* @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] lhs_stride_y Stride of the LHS matrix in Y dimension (in bytes)
* @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS matrix
* @param[in] rhs_ptr Pointer to the RHS reshaped matrix. Supported data type: same as @p lhs_ptr
* @param[in] rhs_stride_x Stride of the RHS reshaped matrix in X dimension (in bytes)
* @param[in] rhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] rhs_stride_y Stride of the RHS reshaped matrix in Y dimension (in bytes)
* @param[in] rhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS reshaped matrix
* @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
* @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
* @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] bias_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
* @param[in] bias_step_y (Optional) bias_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes)
* @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
* @param[in] lhs_stride_z Stride of the LHS matrix in Z dimension (in bytes)
* @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes)
* @param[in] bias_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] lhs_cross_plane_pad (Optional) Bottom paddings for LHS matrix in unit of elements (only if defined REINTERPRET_INPUT_AS_3D)
* @param[in] dst_cross_plane_pad (Optional) Bottom paddings for the output matrix in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
* @param[in] M Number of rows in LHS matrix not reshaped.
* @param[in] N Number of columns in RHS matrix not reshaped.
* @param[in] K Number of columns in LHS matrix and rows in RHS matrix not reshaped.
*/
__kernel void gemm_mm_reshaped_only_rhs_nt(IMAGE_DECLARATION(lhs),
IMAGE_DECLARATION(rhs),
#if defined(BETA)
IMAGE_DECLARATION(bias),
#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint lhs_stride_z,
uint rhs_stride_z,
#if defined(BETA)
uint bias_stride_z,
#endif //defined(BETA)
uint dst_stride_z
#if defined(REINTERPRET_INPUT_AS_3D)
,
uint lhs_cross_plane_pad
#endif // REINTERPRET_INPUT_AS_3D
#if defined(REINTERPRET_OUTPUT_AS_3D)
,
uint dst_cross_plane_pad
#endif // REINTERPRET_OUTPUT_AS_3D
,
const int M,
const int N,
const int K)
{
// Block size
#define RHS_BLOCK_SIZE ((K0) * (N0))
// RHS offset and step X
#if defined(RHS_INTERLEAVE)
#define RHS_OFFSET_X (N0)
#define RHS_STEP_X ((N0) * (H0))
#define RHS_STEP_LOOP (1)
#else // defined(RHS_INTERLEAVE)
#define RHS_OFFSET_X (RHS_BLOCK_SIZE)
#define RHS_STEP_X (N0)
#define RHS_STEP_LOOP (H0)
#endif // defined(RHS_INTERLEAVE)
uint x = get_global_id(0);
uint y = get_global_id(1);
uint z = get_global_id(2);
const bool cond_y = y == 0;
const bool cond_x = ((x + 1) * N0 >= N);
#if defined(DUMMY_WORK_ITEMS)
if((x * N0 >= N) || (y * M0 >= M))
{
return;
}
#endif // defined(DUMMY_WORK_ITEMS)
// Compute LHS matrix address
uint lhs_offset = lhs_offset_first_element_in_bytes + COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * (uint)lhs_stride_y;
// Compute RHS reshaped matrix address
uint rhs_offset = rhs_offset_first_element_in_bytes + (x % H0) * (uint)RHS_OFFSET_X * sizeof(DATA_TYPE) + (x / (uint)H0) * rhs_stride_y;
#if defined(MATRIX_B_DEPTH)
// Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
rhs_offset += (z % MATRIX_B_DEPTH) * rhs_stride_z;
#else // defined(MATRIX_B_DEPTH)
rhs_offset += z * rhs_stride_z;
#endif // defined(MATRIX_B_DEPTH)
REPEAT_VAR_INIT_TO_CONST(8, uint, zin, 0); //uint zin0=0,zin1=0,zin2=0,... zin7=0;
REPEAT_VAR_INIT_TO_CONST(16, uint, zero, 0); //uint zero0=0,zero1=0,zero2=0,... zero7=0;
#if defined(REINTERPRET_INPUT_AS_3D)
// The plane (zin) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
CALCULATE_Z_OFFSET(M0, uint, zin, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply lhs_stride_z by DEPTH_GEMM3D
lhs_offset += z * lhs_stride_z * DEPTH_GEMM3D;
#else // defined(REINTERPRET_INPUT_AS_3D)
// Add offset for batched GEMM
lhs_offset += z * lhs_stride_z;
#endif // defined(REINTERPRET_INPUT_AS_3D)
// Initialize the accumulators
REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE, N0), c, 0); //VEC_DATA_TYPE(DATA_TYPE, N0) c0=0,c1=0,c2=0,... c(N0-1)=0;
int i = 0;
for(; i <= (K - K0); i += K0)
{
// Supported cases (M0, K0):
// 1,2 - 1,3 - 1,4 - 1,8 - 1,16
// 2,2 - 2,3 - 2,4 - 2,8 - 2,16
// 3,2 - 3,3 - 3,4 - 3,8 - 3,16
// 4,2 - 4,3 - 4,4 - 4,8 - 4,16
// 5,2 - 5,3 - 5,4 - 5,8 - 5,16
// 6,2 - 6,3 - 6,4 - 6,8 - 6,16
// 7,2 - 7,3 - 7,4 - 7,8 - 7,16
// 8,2 - 8,3 - 8,4 - 8,8 - 8,16
// Load values from LHS matrix
LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zin);
VEC_DATA_TYPE(DATA_TYPE, N0)
b0;
b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 0 * RHS_STEP_X * sizeof(DATA_TYPE)));
VFMA_M0xN0(0, a, b0, c);
b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 1 * RHS_STEP_X * sizeof(DATA_TYPE)));
VFMA_M0xN0(1, a, b0, c);
#if K0 > 2
b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 2 * RHS_STEP_X * sizeof(DATA_TYPE)));
VFMA_M0xN0(2, a, b0, c);
#endif // K0 > 2
#if K0 > 3
b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 3 * RHS_STEP_X * sizeof(DATA_TYPE)));
VFMA_M0xN0(3, a, b0, c);
#endif // K0 > 3
#if K0 > 4
b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 4 * RHS_STEP_X * sizeof(DATA_TYPE)));
VFMA_M0xN0(4, a, b0, c);
b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 5 * RHS_STEP_X * sizeof(DATA_TYPE)));
VFMA_M0xN0(5, a, b0, c);
b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 6 * RHS_STEP_X * sizeof(DATA_TYPE)));
VFMA_M0xN0(6, a, b0, c);
b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 7 * RHS_STEP_X * sizeof(DATA_TYPE)));
VFMA_M0xN0(7, a, b0, c);
#endif // K0 > 4
#if K0 > 8
b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 8 * RHS_STEP_X * sizeof(DATA_TYPE)));
VFMA_M0xN0(8, a, b0, c);
b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 9 * RHS_STEP_X * sizeof(DATA_TYPE)));
VFMA_M0xN0(9, a, b0, c);
b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 10 * RHS_STEP_X * sizeof(DATA_TYPE)));
VFMA_M0xN0(A, a, b0, c);
b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 11 * RHS_STEP_X * sizeof(DATA_TYPE)));
VFMA_M0xN0(B, a, b0, c);
b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 12 * RHS_STEP_X * sizeof(DATA_TYPE)));
VFMA_M0xN0(C, a, b0, c);
b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 13 * RHS_STEP_X * sizeof(DATA_TYPE)));
VFMA_M0xN0(D, a, b0, c);
b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 14 * RHS_STEP_X * sizeof(DATA_TYPE)));
VFMA_M0xN0(E, a, b0, c);
b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 15 * RHS_STEP_X * sizeof(DATA_TYPE)));
VFMA_M0xN0(F, a, b0, c);
#endif // K0 > 8
lhs_offset += K0 * sizeof(DATA_TYPE);
rhs_offset += K0 * RHS_STEP_X * RHS_STEP_LOOP * sizeof(DATA_TYPE);
}
// Left-over accumulations
for(; i < K; ++i)
{
// Load values from LHS matrix
VEC_DATA_TYPE(DATA_TYPE, 2)
a0 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 0 * lhs_stride_y + zin0));
#if M0 > 1
VEC_DATA_TYPE(DATA_TYPE, 2)
a1 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 1 * lhs_stride_y + zin1));
#endif // M0 > 1
#if M0 > 2
VEC_DATA_TYPE(DATA_TYPE, 2)
a2 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 2 * lhs_stride_y + zin2));
#endif // M0 > 2
#if M0 > 3
VEC_DATA_TYPE(DATA_TYPE, 2)
a3 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 3 * lhs_stride_y + zin3));
#endif // M0 > 3
#if M0 > 4
VEC_DATA_TYPE(DATA_TYPE, 2)
a4 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 4 * lhs_stride_y + zin4));
#endif // M0 > 4
#if M0 > 5
VEC_DATA_TYPE(DATA_TYPE, 2)
a5 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 5 * lhs_stride_y + zin5));
#endif // M0 > 5
#if M0 > 6
VEC_DATA_TYPE(DATA_TYPE, 2)
a6 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 6 * lhs_stride_y + zin6));
#endif // M0 > 6
#if M0 > 7
VEC_DATA_TYPE(DATA_TYPE, 2)
a7 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 7 * lhs_stride_y + zin7));
#endif // M0 > 7
VEC_DATA_TYPE(DATA_TYPE, N0)
b0;
b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 0 * RHS_STEP_X * sizeof(DATA_TYPE)));
VFMA_M0xN0(0, a, b0, c);
lhs_offset += sizeof(DATA_TYPE);
rhs_offset += RHS_STEP_X * sizeof(DATA_TYPE);
}
__global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * dst_stride_y);
REPEAT_VAR_INIT_TO_CONST(8, uint, zout, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0;
#if defined(REINTERPRET_OUTPUT_AS_3D)
// The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += z * dst_stride_z;
#endif // defined(REINTERPRET_OUTPUT_AS_3D)
// Multiply by the weight of matrix-matrix product and store the result
#if defined(ALPHA)
SCALE_BLOCK(M0, DATA_TYPE, c, ALPHA);
#endif // defined(ALPHA)
// Add beta*bias
#if defined(BETA)
#if defined(BROADCAST_BIAS)
__global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE));
LOAD_BLOCK_BOUNDARY_AWARE(1, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, 1, PARTIAL_STORE_N0, false, cond_x);
#ifndef UNIT_BETA
SCALE_BLOCK(1, DATA_TYPE, bias, BETA);
#endif // UNIT_BIAS
// c = c + bias[broadcasted]
ADD_BLOCK_BROADCAST(M0, c, bias0);
#else // defined(BROADCAST_BIAS)
__global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * bias_stride_y) + z * bias_stride_z;
LOAD_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#ifndef UNIT_BETA
SCALE_BLOCK(M0, DATA_TYPE, bias, BETA);
#endif // UNIT_BIAS
// c = c + bias
ADD_BLOCK(M0, c, bias);
#endif // defined(BROADCAST_BIAS)
#endif // defined(BETA)
#if defined(ACTIVATION_TYPE)
ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE, VEC_SIZE, c, A_VAL, B_VAL);
#endif // defined(ACTIVATION_TYPE)
// Store output block
STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#undef RHS_BLOCK_SIZE
#undef RHS_OFFSET_X
#undef RHS_STEP_X
#undef RHS_STEP_LOOP
}
#endif // defined(GEMM_MM_RESHAPED_ONLY_RHS_NT)
#if defined(OPENCL_IMAGE_SUPPORT) && defined(GEMM_MM_RESHAPED_ONLY_RHS_NT_TEXTURE)
/** This OpenCL kernel computes the matrix multiplication between 2 matrices.
* The LHS matrix is NOT reshaped
* The RHS is reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the block K0xN0 is NOT transposed
* @note This kernel is duplicated in /experimental/gemm_fused_post_ops/act_eltwise_op_act/gemm_mm_reshaped_only_rhs.cl
*
* @note -DOPENCL_IMAGE_SUPPORT must be passed at compile time in order to compile this OpenCL kernel
* @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time.
* @note The GEMM's dimensions (M,N and K) must be passed at runtime as kernel parameters.
* @note The height of the RHS matrix, defined before creating the OpenCL image object from the OpenCL buffer, should be passed at compile time using -DRHS_HEIGHT=<value> (e.g. -DRHS_HEIGHT=32)
* Since we cannot create a 3d image from a buffer, the third dimension could be collapsed with the second dimension so RHS_HEIGHT
* could be different from the value returned by get_image_height(rhs_img).
* @note The block's dimensions used for reshaping the RHS matrix (N0 and K0) must be passed at compile time using -DN0 and -DK0 (e.g. -DN0=8, -DK0=4).
* @note The number of M0 rows to process must be passed at compile time using -DM0 (e.g. -DM0=2)
* @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2)
* @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time.
* @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1)
* @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1)
* @note Only the following configurations of M0, N0 and K0 are currently supported:
* - M0 = 1, 2, 3, 4, 5, 6, 7, 8
* - N0 = 4, 8, 16
* - K0 = 4, 8, 16
* - H0 >= 1
*
* @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
* The activation function is performed after the bias addition
* @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time:
* -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
* -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor.
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix
*
* @param[in] lhs_ptr Pointer to the LHS matrix. Supported data type: F32
* @param[in] lhs_stride_x Stride of the LHS matrix in X dimension (in bytes)
* @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] lhs_stride_y Stride of the LHS matrix in Y dimension (in bytes)
* @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS matrix
* @param[in] rhs_img The RHS reshaped matrix as OpenCL image object. Supported data type: same as @p lhs_ptr
* @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
* @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
* @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] bias_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
* @param[in] bias_step_y (Optional) bias_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes)
* @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
* @param[in] lhs_stride_z Stride of the LHS matrix in Z dimension (in bytes)
* @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes)
* @param[in] bias_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] lhs_cross_plane_pad (Optional) Bottom paddings for LHS matrix in unit of elements (only if defined REINTERPRET_INPUT_AS_3D)
* @param[in] dst_cross_plane_pad (Optional) Bottom paddings for the output matrix in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
* @param[in] M Number of rows in LHS matrix not reshaped.
* @param[in] N Number of columns in RHS matrix not reshaped.
* @param[in] K Number of columns in LHS matrix and rows in RHS matrix not reshaped.
*/
__kernel void gemm_mm_reshaped_only_rhs_nt_texture(IMAGE_DECLARATION(lhs),
__read_only image2d_t rhs_img,
#if defined(BETA)
IMAGE_DECLARATION(bias),
#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint lhs_stride_z,
uint rhs_stride_z,
#if defined(BETA)
uint bias_stride_z,
#endif //defined(BETA)
uint dst_stride_z
#if defined(REINTERPRET_INPUT_AS_3D)
,
uint lhs_cross_plane_pad
#endif // REINTERPRET_INPUT_AS_3D
#if defined(REINTERPRET_OUTPUT_AS_3D)
,
uint dst_cross_plane_pad
#endif // REINTERPRET_OUTPUT_AS_3D
,
const int M,
const int N,
const int K)
{
// Pixel unit
#define PIXEL_UNIT CONVERT_VECTOR_SIZE_TO_PIXEL_UNIT(N0)
// Block size
#define RHS_BLOCK_SIZE ((K0) * (PIXEL_UNIT))
// RHS offset and step X
#if defined(RHS_INTERLEAVE)
#define RHS_OFFSET_X (PIXEL_UNIT)
#define RHS_STEP_X ((PIXEL_UNIT) * (H0))
#define RHS_STEP_LOOP 1
#else // defined(RHS_INTERLEAVE)
#define RHS_OFFSET_X (RHS_BLOCK_SIZE)
#define RHS_STEP_X (PIXEL_UNIT)
#define RHS_STEP_LOOP (H0)
#endif // defined(RHS_INTERLEAVE)
uint x = get_global_id(0);
uint y = get_global_id(1);
uint z = get_global_id(2);
const bool cond_y = y == 0;
const bool cond_x = ((x + 1) * N0 >= N);
#if defined(DUMMY_WORK_ITEMS)
if((x * N0 >= N) || (y * M0 >= M))
{
return;
}
#endif // defined(DUMMY_WORK_ITEMS)
// Compute LHS matrix address
uint lhs_offset = lhs_offset_first_element_in_bytes + COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * (uint)lhs_stride_y;
#if defined(MATRIX_B_DEPTH)
// Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
const uint z_rhs = (z % MATRIX_B_DEPTH);
#else // defined(MATRIX_B_DEPTH)
const uint z_rhs = z;
#endif // defined(MATRIX_B_DEPTH)
// Compute RHS matrix coordinates
uint x_rhs = (x % H0) * (uint)RHS_OFFSET_X;
const uint y_rhs = (x / (uint)H0) + z_rhs * RHS_HEIGHT;
REPEAT_VAR_INIT_TO_CONST(8, uint, zin, 0);
REPEAT_VAR_INIT_TO_CONST(16, uint, zero, 0);
#if defined(REINTERPRET_INPUT_AS_3D)
// The plane (zin) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
CALCULATE_Z_OFFSET(M0, uint, zin, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply lhs_stride_z by DEPTH_GEMM3D
lhs_offset += z * lhs_stride_z * DEPTH_GEMM3D;
#else // defined(REINTERPRET_INPUT_AS_3D)
// Add offset for batched GEMM
lhs_offset += z * lhs_stride_z;
#endif // defined(REINTERPRET_INPUT_AS_3D)
// Initialize the accumulators
REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE, N0), c, 0);
int i = 0;
for(; i <= (K - K0); i += K0)
{
// Load values from LHS matrix
LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zin);
VEC_DATA_TYPE(DATA_TYPE, N0)
b0;
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 0 * RHS_STEP_X), (y_rhs));
VFMA_M0xN0(0, a, b0, c);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 1 * RHS_STEP_X), (y_rhs));
VFMA_M0xN0(1, a, b0, c);
#if K0 > 2
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 2 * RHS_STEP_X), (y_rhs));
VFMA_M0xN0(2, a, b0, c);
#endif // K0 > 2
#if K0 > 3
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 3 * RHS_STEP_X), (y_rhs));
VFMA_M0xN0(3, a, b0, c);
#endif // K0 > 3
#if K0 > 4
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 4 * RHS_STEP_X), (y_rhs));
VFMA_M0xN0(4, a, b0, c);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 5 * RHS_STEP_X), (y_rhs));
VFMA_M0xN0(5, a, b0, c);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 6 * RHS_STEP_X), (y_rhs));
VFMA_M0xN0(6, a, b0, c);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 7 * RHS_STEP_X), (y_rhs));
VFMA_M0xN0(7, a, b0, c);
#endif // K0 > 4
#if K0 > 8
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 8 * RHS_STEP_X), (y_rhs));
VFMA_M0xN0(8, a, b0, c);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 9 * RHS_STEP_X), (y_rhs));
VFMA_M0xN0(9, a, b0, c);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 10 * RHS_STEP_X), (y_rhs));
VFMA_M0xN0(A, a, b0, c);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 11 * RHS_STEP_X), (y_rhs));
VFMA_M0xN0(B, a, b0, c);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 12 * RHS_STEP_X), (y_rhs));
VFMA_M0xN0(C, a, b0, c);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 13 * RHS_STEP_X), (y_rhs));
VFMA_M0xN0(D, a, b0, c);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 14 * RHS_STEP_X), (y_rhs));
VFMA_M0xN0(E, a, b0, c);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 15 * RHS_STEP_X), (y_rhs));
VFMA_M0xN0(F, a, b0, c);
#endif // K0 > 8
lhs_offset += K0 * sizeof(DATA_TYPE);
x_rhs += K0 * RHS_STEP_X * RHS_STEP_LOOP;
}
// Left-over accumulations
for(; i < K; ++i)
{
// Load values from LHS matrix
VEC_DATA_TYPE(DATA_TYPE, 2)
a0 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 0 * lhs_stride_y + zin0));
#if M0 > 1
VEC_DATA_TYPE(DATA_TYPE, 2)
a1 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 1 * lhs_stride_y + zin1));
#endif // M0 > 1
#if M0 > 2
VEC_DATA_TYPE(DATA_TYPE, 2)
a2 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 2 * lhs_stride_y + zin2));
#endif // M0 > 2
#if M0 > 3
VEC_DATA_TYPE(DATA_TYPE, 2)
a3 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 3 * lhs_stride_y + zin3));
#endif // M0 > 3
#if M0 > 4
VEC_DATA_TYPE(DATA_TYPE, 2)
a4 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 4 * lhs_stride_y + zin4));
#endif // M0 > 4
#if M0 > 5
VEC_DATA_TYPE(DATA_TYPE, 2)
a5 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 5 * lhs_stride_y + zin5));
#endif // M0 > 5
#if M0 > 6
VEC_DATA_TYPE(DATA_TYPE, 2)
a6 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 6 * lhs_stride_y + zin6));
#endif // M0 > 6
#if M0 > 7
VEC_DATA_TYPE(DATA_TYPE, 2)
a7 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 7 * lhs_stride_y + zin7));
#endif // M0 > 7
VEC_DATA_TYPE(DATA_TYPE, N0)
b0;
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 0 * RHS_STEP_X), (y_rhs));
VFMA_M0xN0(0, a, b0, c);
lhs_offset += sizeof(DATA_TYPE);
x_rhs += RHS_STEP_X;
}
__global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * dst_stride_y);
REPEAT_VAR_INIT_TO_CONST(8, uint, zout, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0;
#if defined(REINTERPRET_OUTPUT_AS_3D)
// The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += z * dst_stride_z;
#endif // defined(REINTERPRET_OUTPUT_AS_3D)
// Multiply by the weight of matrix-matrix product and store the result
#if defined(ALPHA)
SCALE_BLOCK(M0, DATA_TYPE, c, ALPHA);
#endif // defined(ALPHA)
// Add beta*bias
#if defined(BETA)
#if defined(BROADCAST_BIAS)
__global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE));
LOAD_BLOCK_BOUNDARY_AWARE(1, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, 1, PARTIAL_STORE_N0, false, cond_x);
#ifndef UNIT_BETA
SCALE_BLOCK(1, DATA_TYPE, bias, BETA);
#endif // UNIT_BIAS
// c = c + bias[broadcasted]
ADD_BLOCK_BROADCAST(M0, c, bias0);
#else // defined(BROADCAST_BIAS)
__global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * bias_stride_y) + z * bias_stride_z;
LOAD_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#ifndef UNIT_BETA
SCALE_BLOCK(M0, DATA_TYPE, bias, BETA);
#endif // UNIT_BIAS
// c = c + bias
ADD_BLOCK(M0, c, bias);
#endif // defined(BROADCAST_BIAS)
#endif // defined(BETA)
#if defined(ACTIVATION_TYPE)
ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE, VEC_SIZE, c, A_VAL, B_VAL);
#endif // defined(ACTIVATION_TYPE)
// Store output block
STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#undef RHS_BLOCK_SIZE
#undef RHS_OFFSET_X
#undef RHS_STEP_X
#undef RHS_STEP_LOOP
}
#endif // defined(OPENCL_IMAGE_SUPPORT) && defined(GEMM_MM_RESHAPED_ONLY_RHS_NT_TEXTURE)
#endif // defined(M0) && defined(N0) && defined(K0) && defined(H0) && defined(DATA_TYPE)
#if defined(M0) && defined(N0) && defined(K0) && defined(V0) && defined(H0) && defined(DATA_TYPE) && defined(DATA_TYPE_ACCUMULATOR)
#if defined(MIXED_PRECISION)
#if K0 == 2
#define ARM_DOT_K0(a, b, c) \
({ \
c += a.s0 * b.s0; \
c += a.s1 * b.s1; \
})
#elif K0 == 3 // K0 == 3
#define ARM_DOT_K0(a, b, c) \
({ \
c += a.s0 * b.s0; \
c += a.s1 * b.s1; \
c += a.s2 * b.s2; \
})
#elif K0 == 4 // K0 == 4
#define ARM_DOT_K0(a, b, c) \
({ \
c += a.s0 * b.s0; \
c += a.s1 * b.s1; \
c += a.s2 * b.s2; \
c += a.s3 * b.s3; \
})
#elif K0 == 8 // K0 == 8
#define ARM_DOT_K0(a, b, c) \
({ \
c += a.s0 * b.s0; \
c += a.s1 * b.s1; \
c += a.s2 * b.s2; \
c += a.s3 * b.s3; \
c += a.s4 * b.s4; \
c += a.s5 * b.s5; \
c += a.s6 * b.s6; \
c += a.s7 * b.s7; \
})
#elif K0 == 16 // K0 == 16
#define ARM_DOT_K0(a, b, c) \
({ \
c += a.s0 * b.s0; \
c += a.s1 * b.s1; \
c += a.s2 * b.s2; \
c += a.s3 * b.s3; \
c += a.s4 * b.s4; \
c += a.s5 * b.s5; \
c += a.s6 * b.s6; \
c += a.s7 * b.s7; \
c += a.s8 * b.s8; \
c += a.s9 * b.s9; \
c += a.sA * b.sA; \
c += a.sB * b.sB; \
c += a.sC * b.sC; \
c += a.sD * b.sD; \
c += a.sE * b.sE; \
c += a.sF * b.sF; \
})
#else // K0 not supported
#error "K0 value not supported"
#endif // K0 conditions
#else // defined(MIXED_PRECISION)
#if K0 == 2
#define ARM_DOT_K0(a, b, c) \
({ \
c = fma(a.s0, b.s0, c); \
c = fma(a.s1, b.s1, c); \
})
#elif K0 == 3 // K0 == 3
#define ARM_DOT_K0(a, b, c) \
({ \
c = fma(a.s0, b.s0, c); \
c = fma(a.s1, b.s1, c); \
c = fma(a.s2, b.s2, c); \
})
#elif K0 == 4 // K0 == 4
#define ARM_DOT_K0(a, b, c) \
({ \
c = fma(a.s0, b.s0, c); \
c = fma(a.s1, b.s1, c); \
c = fma(a.s2, b.s2, c); \
c = fma(a.s3, b.s3, c); \
})
#elif K0 == 8 // K0 == 8
#define ARM_DOT_K0(a, b, c) \
({ \
c = fma(a.s0, b.s0, c); \
c = fma(a.s1, b.s1, c); \
c = fma(a.s2, b.s2, c); \
c = fma(a.s3, b.s3, c); \
c = fma(a.s4, b.s4, c); \
c = fma(a.s5, b.s5, c); \
c = fma(a.s6, b.s6, c); \
c = fma(a.s7, b.s7, c); \
})
#elif K0 == 16 // K0 == 16
#define ARM_DOT_K0(a, b, c) \
({ \
c = fma(a.s0, b.s0, c); \
c = fma(a.s1, b.s1, c); \
c = fma(a.s2, b.s2, c); \
c = fma(a.s3, b.s3, c); \
c = fma(a.s4, b.s4, c); \
c = fma(a.s5, b.s5, c); \
c = fma(a.s6, b.s6, c); \
c = fma(a.s7, b.s7, c); \
c = fma(a.s8, b.s8, c); \
c = fma(a.s9, b.s9, c); \
c = fma(a.sA, b.sA, c); \
c = fma(a.sB, b.sB, c); \
c = fma(a.sC, b.sC, c); \
c = fma(a.sD, b.sD, c); \
c = fma(a.sE, b.sE, c); \
c = fma(a.sF, b.sF, c); \
})
#else // K0 not supported
#error "K0 value not supported"
#endif // K0 conditions
#endif // defined(MIXED_PRECISION)
#if defined(ARM_DOT_K0XN0)
#undef ARM_DOT_K0XN0
#endif // defined(ARM_DOT_K0XN0)
#if N0 == 2
#define ARM_DOT_K0XN0(a, b, c) \
({ \
ARM_DOT_K0((a), (b##0), (c.s0)); \
ARM_DOT_K0((a), (b##1), (c.s1)); \
})
#elif N0 == 3 // N0 == 3
#define ARM_DOT_K0XN0(a, b, c) \
({ \
ARM_DOT_K0((a), (b##0), (c.s0)); \
ARM_DOT_K0((a), (b##1), (c.s1)); \
ARM_DOT_K0((a), (b##2), (c.s2)); \
})
#elif N0 == 4 // N0 == 4
#define ARM_DOT_K0XN0(a, b, c) \
({ \
ARM_DOT_K0((a), (b##0), (c.s0)); \
ARM_DOT_K0((a), (b##1), (c.s1)); \
ARM_DOT_K0((a), (b##2), (c.s2)); \
ARM_DOT_K0((a), (b##3), (c.s3)); \
})
#elif N0 == 8 // N0 == 8
#define ARM_DOT_K0XN0(a, b, c) \
({ \
ARM_DOT_K0((a), (b##0), (c.s0)); \
ARM_DOT_K0((a), (b##1), (c.s1)); \
ARM_DOT_K0((a), (b##2), (c.s2)); \
ARM_DOT_K0((a), (b##3), (c.s3)); \
ARM_DOT_K0((a), (b##4), (c.s4)); \
ARM_DOT_K0((a), (b##5), (c.s5)); \
ARM_DOT_K0((a), (b##6), (c.s6)); \
ARM_DOT_K0((a), (b##7), (c.s7)); \
})
#elif N0 == 16 // N0 == 16
#define ARM_DOT_K0XN0(a, b, c) \
({ \
ARM_DOT_K0((a), (b##0), (c.s0)); \
ARM_DOT_K0((a), (b##1), (c.s1)); \
ARM_DOT_K0((a), (b##2), (c.s2)); \
ARM_DOT_K0((a), (b##3), (c.s3)); \
ARM_DOT_K0((a), (b##4), (c.s4)); \
ARM_DOT_K0((a), (b##5), (c.s5)); \
ARM_DOT_K0((a), (b##6), (c.s6)); \
ARM_DOT_K0((a), (b##7), (c.s7)); \
ARM_DOT_K0((a), (b##8), (c.s8)); \
ARM_DOT_K0((a), (b##9), (c.s9)); \
ARM_DOT_K0((a), (b##A), (c.sA)); \
ARM_DOT_K0((a), (b##B), (c.sB)); \
ARM_DOT_K0((a), (b##C), (c.sC)); \
ARM_DOT_K0((a), (b##D), (c.sD)); \
ARM_DOT_K0((a), (b##E), (c.sE)); \
ARM_DOT_K0((a), (b##F), (c.sF)); \
})
#else // N0 not supported
#error "N0 value not supported"
#endif // N0 conditions
#if defined(GEMM_MM_RESHAPED_LHS_NT_RHS_T)
/** This OpenCL kernel computes the matrix multiplication between 2 matrices.
* The LHS matrix must be reshaped with @ref CLGEMMReshapeLHSMatrixKernel and the M0xK0 must be NOT transposed
* The RHS matrix must be reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the K0xN0 must be transposed
* @note This kernel is duplicated in /experimental/gemm_fused_post_ops/act_eltwise_op_act/gemm_mm_reshaped.cl
*
* @note The data type must be passed at compile time using -DDATA_TYPE (e.g. -DDATA_TYPE=float)
* @note The data type used for the accumulators must be passed at compile time using -DDATA_TYPE_ACCUMULATOR (e.g. -DDATA_TYPE_ACCUMULATOR=float)
* @note The F16 computation also supports mixed precision through the option -DMIXED_PRECISION passed at compile time. If enabled, DATA_TYPE_ACCUMULATOR should be set to float
* @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time.
* @note The GEMM's dimensions M, N and K must be passed at compile time using -DM, -DN and -DK (e.g. -DM=52, -DN=90 and -DK=24).
* @note The block's dimensions used for reshaping the LHS matrix and the RHS matrix (M0, N0 and K0) must be passed at compile time using -DM0, -DN0 and -DK0 (e.g. -DM0=4, -DN0=8, -DK0=4).
* @note The number of M0xK0 vertical blocks stored on the same output row of the reshaped LHS matrix must be passed at compile time using -DV0 (e.g. -DV0=2)
* @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2)
* @note If the M0xK0 blocks in the reshaped LHS matrix have been interleaved, the option -DLHS_INTERLEAVE must passed at compile time.
* @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time.
* @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1)
* @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1)
* @note Only the following configurations of M0, N0 and K0 are currently supported:
* - M0 = 2, 3, 4, 5, 6, 7, 8
* - N0 = 2, 3, 4, 8, 16
* - K0 = 2, 3, 4, 8, 16
* - V0 >= 1
* - H0 >= 1
*
* @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
* The activation function is performed after the bias addition
* @note In case the output has to be reinterpreted as a 3D tensor (e.g. output of convolution layer), the following information must be passed at compile time:
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
* -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor.
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix NOT reshaped
*
* @param[in] lhs_ptr Pointer to the LHS reshaped matrix. Supported data type: F16/F32
* @param[in] lhs_stride_x Stride of the LHS reshaped matrix in X dimension (in bytes)
* @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] lhs_stride_y Stride of the LHS reshaped matrix in Y dimension (in bytes)
* @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS reshaped matrix
* @param[in] rhs_ptr Pointer to the RHS reshaped matrix. Supported data type: same as @p lhs_ptr
* @param[in] rhs_stride_x Stride of the RHS reshaped matrix in X dimension (in bytes)
* @param[in] rhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] rhs_stride_y Stride of the RHS reshaped matrix in Y dimension (in bytes)
* @param[in] rhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS reshaped matrix
* @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
* @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
* @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] bias_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
* @param[in] bias_step_y (Optional) bias_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes)
* @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
* @param[in] lhs_stride_z Stride of the LHS reshaped matrix in Z dimension (in bytes)
* @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes)
* @param[in] bias_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] dst_cross_plane_pad (Optional) Bottom paddings in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
* @param[in] M Number of rows in LHS matrix not reshaped.
* @param[in] N Number of columns in RHS matrix not reshaped.
* @param[in] K Number of columns in LHS matrix and rows in RHS matrix not reshaped.
*/
__kernel void gemm_mm_reshaped_lhs_nt_rhs_t(IMAGE_DECLARATION(lhs),
IMAGE_DECLARATION(rhs),
#if defined(BETA)
IMAGE_DECLARATION(bias),
#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint lhs_stride_z,
uint rhs_stride_z,
#if defined(BETA)
uint bias_stride_z,
#endif //defined(BETA)
uint dst_stride_z
#if defined(REINTERPRET_OUTPUT_AS_3D)
,
uint dst_cross_plane_pad
#endif // REINTERPRET_OUTPUT_AS_3D
,
const int M,
const int N,
const int K)
{
// Block size
#define LHS_BLOCK_SIZE ((K0) * (M0))
#if defined(LHS_INTERLEAVE)
#define LHS_OFFSET_X (K0)
#define LHS_STEP_X ((K0) * (V0))
#define LHS_STEP_LOOP (1)
#else // defined(INTERLEAVE)
#define LHS_OFFSET_X (LHS_BLOCK_SIZE)
#define LHS_STEP_X (K0)
#define LHS_STEP_LOOP (V0)
#endif // defined(INTERLEAVE)
// Block size
#define RHS_BLOCK_SIZE ((K0) * (N0))
// RHS offset and step X
#if defined(RHS_INTERLEAVE)
#define RHS_OFFSET_X (K0)
#define RHS_STEP_X ((K0) * (H0))
#define RHS_STEP_LOOP (1)
#else // defined(RHS_INTERLEAVE)
#define RHS_OFFSET_X (RHS_BLOCK_SIZE)
#define RHS_STEP_X (K0)
#define RHS_STEP_LOOP (H0)
#endif // defined(RHS_INTERLEAVE)
#if defined(DUMMY_WORK_ITEMS)
if((get_global_id(0) * N0 >= N) || (get_global_id(1) * M0 >= M))
{
return;
}
#endif // defined(DUMMY_WORK_ITEMS)
// Compute LHS matrix address
__global uchar *lhs_addr = lhs_ptr + lhs_offset_first_element_in_bytes + (get_global_id(1) % V0) * (uint)LHS_OFFSET_X * sizeof(DATA_TYPE) + (get_global_id(1) / V0) * (uint)lhs_stride_y +
(get_global_id(2) * lhs_stride_z);
// Compute RHS matrix address
__global uchar *rhs_addr = rhs_ptr + rhs_offset_first_element_in_bytes + (get_global_id(0) % H0) * (uint)RHS_OFFSET_X * sizeof(DATA_TYPE) + (get_global_id(0) / (uint)H0) * rhs_stride_y;
#if defined(MATRIX_B_DEPTH)
// Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
rhs_addr += (get_global_id(2) % MATRIX_B_DEPTH) * rhs_stride_z;
#else // defined(MATRIX_B_DEPTH)
rhs_addr += get_global_id(2) * rhs_stride_z;
#endif // defined(MATRIX_B_DEPTH)
// Initialize the accumulators
REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE_ACCUMULATOR, N0), c, 0);
REPEAT_VAR_INIT_TO_CONST(M0, uint, zlhs, 0); //uint zlhs0=0,zlhs1=0,zlhs2=0,... zlhs7=0;
REPEAT_VAR_INIT_TO_CONST(16, uint, zero, 0);
for(int i = 0; i < K; i += K0)
{
// Supported cases (M0, K0):
// 1,2 - 1,3 - 1,4 - 1,8 - 1,16
// 2,2 - 2,3 - 2,4 - 2,8 - 2,16
// 3,2 - 3,3 - 3,4 - 3,8 - 3,16
// 4,2 - 4,3 - 4,4 - 4,8 - 4,16
// 5,2 - 5,3 - 5,4 - 5,8 - 5,16
// 6,2 - 6,3 - 6,4 - 6,8 - 6,16
// 7,2 - 7,3 - 7,4 - 7,8 - 7,16
// 8,2 - 8,3 - 8,4 - 8,8 - 8,16
// Load values from LHS matrix
LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_addr, 0, LHS_STEP_X * sizeof(DATA_TYPE), zlhs);
// Load values from RHS matrix
LOAD_BLOCK(N0, K0, DATA_TYPE, b, rhs_addr, 0, RHS_STEP_X * sizeof(DATA_TYPE), zero);
// Accumulate
ARM_DOT_K0XN0(a0, b, c0);
#if M0 > 1
ARM_DOT_K0XN0(a1, b, c1);
#endif // M0 > 1
#if M0 > 2
ARM_DOT_K0XN0(a2, b, c2);
#endif // M0 > 2
#if M0 > 3
ARM_DOT_K0XN0(a3, b, c3);
#endif // M0 > 3
#if M0 > 4
ARM_DOT_K0XN0(a4, b, c4);
#endif // M0 > 4
#if M0 > 5
ARM_DOT_K0XN0(a5, b, c5);
#endif // M0 > 5
#if M0 > 6
ARM_DOT_K0XN0(a6, b, c6);
#endif // M0 > 6
#if M0 > 7
ARM_DOT_K0XN0(a7, b, c7);
#endif // M0 > 7
lhs_addr += (M0 * LHS_STEP_X * LHS_STEP_LOOP) * sizeof(DATA_TYPE);
rhs_addr += (N0 * RHS_STEP_X * RHS_STEP_LOOP) * sizeof(DATA_TYPE);
}
__global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE)) + (get_global_id(1) * (uint)M0 * dst_stride_y);
REPEAT_VAR_INIT_TO_CONST(M0, uint, zout, 0);
const bool cond_y = ((get_global_id(1) + 1) * M0 >= M);
const bool cond_x = ((get_global_id(0) + 1) * N0 >= N);
#if defined(REINTERPRET_OUTPUT_AS_3D)
// The plane (zin) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
CALCULATE_Z_OFFSET(M0, uint, zout, get_global_id(1) * (uint)M0, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += get_global_id(2) * dst_stride_z * DEPTH_GEMM3D;
#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += get_global_id(2) * dst_stride_z;
#endif // defined(REINTERPRET_OUTPUT_AS_3D)
// Multiply by the weight of matrix-matrix product and store the result
#if defined(ALPHA)
SCALE_BLOCK(M0, DATA_TYPE, c, ALPHA);
#endif // defined(ALPHA)
// Add beta*bias
#if defined(BETA)
#if defined(BROADCAST_BIAS)
__global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE));
LOAD_BLOCK_BOUNDARY_AWARE(1, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, 1, PARTIAL_STORE_N0, false, cond_x);
#ifndef UNIT_BETA
SCALE_BLOCK(1, DATA_TYPE, bias, BETA);
#endif // UNIT_BIAS
// c = c + bias[broadcasted]
#if defined(MIXED_PRECISION)
CONVERT_BLOCK(1, N0, DATA_TYPE_ACCUMULATOR, bias, bias_hp);
ADD_BLOCK_BROADCAST(M0, c, bias_hp0);
#else // defined(MIXED_PRECISION)
ADD_BLOCK_BROADCAST(M0, c, bias0);
#endif // defined(MIXED_PRECISION)
#else // defined(BROADCAST_BIAS)
__global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE)) + (get_global_id(1) * (uint)M0 * bias_stride_y) + get_global_id(
2) * bias_stride_z;
LOAD_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#ifndef UNIT_BETA
SCALE_BLOCK(M0, DATA_TYPE, bias, BETA);
#endif // UNIT_BIAS
// c = c + bias
#if defined(MIXED_PRECISION)
CONVERT_BLOCK(M0, N0, DATA_TYPE_ACCUMULATOR, bias, bias_hp);
ADD_BLOCK(M0, c, bias_hp);
#else // defined(MIXED_PRECISION)
ADD_BLOCK(M0, c, bias);
#endif // defined(MIXED_PRECISION)
#endif // defined(BROADCAST_BIAS)
#endif // defined(BETA)
#if defined(ACTIVATION_TYPE)
#if defined(MIXED_PRECISION)
ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE_ACCUMULATOR, VEC_SIZE, c, A_VAL, B_VAL);
#else // defined(MIXED_PRECISION)
ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE, VEC_SIZE, c, A_VAL, B_VAL);
#endif // defined(MIXED_PRECISION)
#endif // defined(ACTIVATION_TYPE)
// Store output block
#if defined(MIXED_PRECISION)
CONVERT_BLOCK(M0, N0, DATA_TYPE, c, c_lp);
STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c_lp, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#else // defined(MIXED_PRECISION)
STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#endif // defined(MIXED_PRECISION)
#undef LHS_BLOCK_SIZE
#undef LHS_OFFSET_X
#undef LHS_STEP_X
#undef RHS_BLOCK_SIZE
#undef RHS_OFFSET_X
#undef RHS_STEP_X
#undef LHS_STEP_LOOP
#undef RHS_STEP_LOOP
}
#endif // defined(GEMM_MM_RESHAPED_LHS_NT_RHS_T)
#if defined(OPENCL_IMAGE_SUPPORT) && defined(GEMM_MM_RESHAPED_LHS_NT_RHS_T_TEXTURE)
/** This OpenCL kernel computes the matrix multiplication between 2 matrices. The RHS matrix is stored in OpenCL image object.
* The LHS matrix must be reshaped with @ref CLGEMMReshapeLHSMatrixKernel and the M0xK0 must be NOT transposed
* The RHS matrix must be reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the K0xN0 must be transposed
* @note This kernel is duplicated in /experimental/gemm_fused_post_ops/act_eltwise_op_act/gemm_mm_reshaped.cl
*
* @note -DOPENCL_IMAGE_SUPPORT must be passed at compile time in order to compile this OpenCL kernel
* @note The data type must be passed at compile time using -DDATA_TYPE (e.g. -DDATA_TYPE=float)
* @note The data type used for the accumulators must be passed at compile time using -DDATA_TYPE_ACCUMULATOR (e.g. -DDATA_TYPE_ACCUMULATOR=float)
* @note The F16 computation also supports mixed precision through the option -DMIXED_PRECISION passed at compile time. If enabled, DATA_TYPE_ACCUMULATOR should be set to float
* @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time.
* @note The GEMM's dimensions M, N and K must be passed at compile time using -DM, -DN and -DK (e.g. -DM=52, -DN=90 and -DK=24).
* @note The height of the RHS matrix, defined before creating the OpenCL image object from the OpenCL buffer, should be passed at compile time using -DRHS_HEIGHT=<value> (e.g. -DRHS_HEIGHT=32)
* Since we cannot create a 3d image from a buffer, the third dimension could be collapsed with the second dimension so RHS_HEIGHT
* could be different from the value returned by get_image_height(rhs_img).
* @note The block's dimensions used for reshaping the LHS matrix and the RHS matrix (M0, N0 and K0) must be passed at compile time using -DM0, -DN0 and -DK0 (e.g. -DM0=4, -DN0=8, -DK0=4).
* @note The number of M0xK0 vertical blocks stored on the same output row of the reshaped LHS matrix must be passed at compile time using -DV0 (e.g. -DV0=2)
* @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2)
* @note If the M0xK0 blocks in the reshaped LHS matrix have been interleaved, the option -DLHS_INTERLEAVE must passed at compile time.
* @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time.
* @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1)
* @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1)
* @note Only the following configurations of M0, N0 and K0 are currently supported:
* - M0 = 2, 3, 4, 5, 6, 7, 8
* - N0 = 4, 8, 16
* - K0 = 4, 8, 16
* - V0 >= 1
* - H0 >= 1
*
* @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
* The activation function is performed after the bias addition
* @note In case the output has to be reinterpreted as a 3D tensor (e.g. output of convolution layer), the following information must be passed at compile time:
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
* -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor.
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix NOT reshaped
*
* @param[in] lhs_ptr Pointer to the LHS reshaped matrix. Supported data type: F32
* @param[in] lhs_stride_x Stride of the LHS reshaped matrix in X dimension (in bytes)
* @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] lhs_stride_y Stride of the LHS reshaped matrix in Y dimension (in bytes)
* @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS reshaped matrix
* @param[in] rhs_img The RHS reshaped matrix as OpenCL image object. Supported data type: same as @p lhs_ptr
* @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
* @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
* @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] bias_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
* @param[in] bias_step_y (Optional) bias_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes)
* @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
* @param[in] lhs_stride_z Stride of the LHS reshaped matrix in Z dimension (in bytes)
* @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes)
* @param[in] bias_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] dst_cross_plane_pad (Optional) Bottom paddings in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
* @param[in] M Number of rows in LHS matrix not reshaped.
* @param[in] N Number of columns in RHS matrix not reshaped.
* @param[in] K Number of columns in LHS matrix and rows in RHS matrix not reshaped.
*/
__kernel void gemm_mm_reshaped_lhs_nt_rhs_t_texture(IMAGE_DECLARATION(lhs),
__read_only image2d_t rhs_img,
#if defined(BETA)
IMAGE_DECLARATION(bias),
#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint lhs_stride_z,
uint rhs_stride_z,
#if defined(BETA)
uint bias_stride_z,
#endif //defined(BETA)
uint dst_stride_z
#if defined(REINTERPRET_OUTPUT_AS_3D)
,
uint dst_cross_plane_pad
#endif // REINTERPRET_OUTPUT_AS_3D
,
const int M,
const int N,
const int K)
{
// Pixel unit
#define PIXEL_UNIT CONVERT_VECTOR_SIZE_TO_PIXEL_UNIT(K0)
// Block size
#define LHS_BLOCK_SIZE ((K0) * (M0))
#if defined(LHS_INTERLEAVE)
#define LHS_OFFSET_X (K0)
#define LHS_STEP_X ((K0) * (V0))
#define LHS_STEP_LOOP (1)
#else // defined(INTERLEAVE)
#define LHS_OFFSET_X (LHS_BLOCK_SIZE)
#define LHS_STEP_X (K0)
#define LHS_STEP_LOOP (V0)
#endif // defined(INTERLEAVE)
// Block size
#define RHS_BLOCK_SIZE (PIXEL_UNIT * (N0))
// RHS offset and step X
#if defined(RHS_INTERLEAVE)
#define RHS_OFFSET_X (PIXEL_UNIT)
#define RHS_STEP_X (PIXEL_UNIT * (H0))
#define RHS_STEP_LOOP (1)
#else // defined(RHS_INTERLEAVE)
#define RHS_OFFSET_X (RHS_BLOCK_SIZE)
#define RHS_STEP_X PIXEL_UNIT
#define RHS_STEP_LOOP (H0)
#endif // defined(RHS_INTERLEAVE)
#if defined(DUMMY_WORK_ITEMS)
if((get_global_id(0) * N0 >= N) || (get_global_id(1) * M0 >= M))
{
return;
}
#endif // defined(DUMMY_WORK_ITEMS)
// Compute LHS matrix address
__global uchar *lhs_addr = lhs_ptr + lhs_offset_first_element_in_bytes + (get_global_id(1) % V0) * (uint)LHS_OFFSET_X * sizeof(DATA_TYPE) + (get_global_id(1) / V0) * (uint)lhs_stride_y +
(get_global_id(2) * lhs_stride_z);
#if defined(MATRIX_B_DEPTH)
// Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
const uint z_rhs = (get_global_id(2) % MATRIX_B_DEPTH);
#else // defined(MATRIX_B_DEPTH)
const uint z_rhs = get_global_id(2);
#endif // defined(MATRIX_B_DEPTH)
// Compute RHS matrix coordinates
uint x_rhs = (get_global_id(0) % H0) * (uint)RHS_OFFSET_X;
const uint y_rhs = (get_global_id(0) / (uint)H0) + z_rhs * RHS_HEIGHT;
// Initialize the accumulators
REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE_ACCUMULATOR, N0), c, 0);
REPEAT_VAR_INIT_TO_CONST(M0, uint, zlhs, 0); //uint zlhs0=0,zlhs1=0,zlhs2=0,... zlhs7=0;
REPEAT_VAR_INIT_TO_CONST(16, uint, zero, 0);
for(int i = 0; i < K; i += K0)
{
// Load values from LHS matrix
LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_addr, 0, LHS_STEP_X * sizeof(DATA_TYPE), zlhs);
// Load values from RHS matrix stored in a cl_image
REPEAT_VAR_INIT_TO_CONST(N0, VEC_DATA_TYPE(DATA_TYPE, K0), b, 0);
LOAD_TEXTURE2D(N0, PIXEL_UNIT, DATA_TYPE, b, rhs_img, x_rhs, y_rhs, RHS_STEP_X, 0);
// Accumulate
ARM_DOT_K0XN0(a0, b, c0);
#if M0 > 1
ARM_DOT_K0XN0(a1, b, c1);
#endif // M0 > 1
#if M0 > 2
ARM_DOT_K0XN0(a2, b, c2);
#endif // M0 > 2
#if M0 > 3
ARM_DOT_K0XN0(a3, b, c3);
#endif // M0 > 3
#if M0 > 4
ARM_DOT_K0XN0(a4, b, c4);
#endif // M0 > 4
#if M0 > 5
ARM_DOT_K0XN0(a5, b, c5);
#endif // M0 > 5
#if M0 > 6
ARM_DOT_K0XN0(a6, b, c6);
#endif // M0 > 6
#if M0 > 7
ARM_DOT_K0XN0(a7, b, c7);
#endif // M0 > 7
lhs_addr += (M0 * LHS_STEP_X * LHS_STEP_LOOP) * sizeof(DATA_TYPE);
x_rhs += N0 * RHS_STEP_X * RHS_STEP_LOOP;
}
__global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE)) + (get_global_id(1) * (uint)M0 * dst_stride_y);
REPEAT_VAR_INIT_TO_CONST(M0, uint, zout, 0);
const bool cond_y = ((get_global_id(1) + 1) * M0 >= M);
const bool cond_x = ((get_global_id(0) + 1) * N0 >= N);
#if defined(REINTERPRET_OUTPUT_AS_3D)
// The plane (zin) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
CALCULATE_Z_OFFSET(M0, uint, zout, get_global_id(1) * (uint)M0, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += get_global_id(2) * dst_stride_z * DEPTH_GEMM3D;
#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += get_global_id(2) * dst_stride_z;
#endif // defined(REINTERPRET_OUTPUT_AS_3D)
// Multiply by the weight of matrix-matrix product and store the result
#if defined(ALPHA)
SCALE_BLOCK(M0, DATA_TYPE, c, ALPHA);
#endif // defined(ALPHA)
// Add beta*bias
#if defined(BETA)
#if defined(BROADCAST_BIAS)
__global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE));
LOAD_BLOCK_BOUNDARY_AWARE(1, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, 1, PARTIAL_STORE_N0, false, cond_x);
#ifndef UNIT_BETA
SCALE_BLOCK(1, DATA_TYPE, bias, BETA);
#endif // UNIT_BIAS
// c = c + bias[broadcasted]
#if defined(MIXED_PRECISION)
CONVERT_BLOCK(1, N0, DATA_TYPE_ACCUMULATOR, bias, bias_hp);
ADD_BLOCK_BROADCAST(M0, c, bias_hp0);
#else // defined(MIXED_PRECISION)
ADD_BLOCK_BROADCAST(M0, c, bias0);
#endif // defined(MIXED_PRECISION)
#else // defined(BROADCAST_BIAS)
__global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE)) + (get_global_id(1) * (uint)M0 * bias_stride_y) + get_global_id(
2) * bias_stride_z;
LOAD_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#ifndef UNIT_BETA
SCALE_BLOCK(M0, DATA_TYPE, bias, BETA);
#endif // UNIT_BIAS
// c = c + bias
#if defined(MIXED_PRECISION)
CONVERT_BLOCK(M0, N0, DATA_TYPE_ACCUMULATOR, bias, bias_hp);
ADD_BLOCK(M0, c, bias_hp);
#else // defined(MIXED_PRECISION)
ADD_BLOCK(M0, c, bias);
#endif // defined(MIXED_PRECISION)
#endif // defined(BROADCAST_BIAS)
#endif // defined(BETA)
#if defined(ACTIVATION_TYPE)
#if defined(MIXED_PRECISION)
ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE_ACCUMULATOR, VEC_SIZE, c, A_VAL, B_VAL);
#else // defined(MIXED_PRECISION)
ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE, VEC_SIZE, c, A_VAL, B_VAL);
#endif // defined(MIXED_PRECISION)
#endif // defined(ACTIVATION_TYPE)
// Store output block
#if defined(MIXED_PRECISION)
CONVERT_BLOCK(M0, N0, DATA_TYPE, c, c_lp);
STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c_lp, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#else // defined(MIXED_PRECISION)
STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#endif // defined(MIXED_PRECISION)
#undef LHS_BLOCK_SIZE
#undef LHS_OFFSET_X
#undef LHS_STEP_X
#undef RHS_BLOCK_SIZE
#undef RHS_OFFSET_X
#undef RHS_STEP_X
#undef PIXEL_UNIT
#undef LHS_STEP_LOOP
#undef RHS_STEP_LOOP
}
#endif // defined(OPENCL_IMAGE_SUPPORT) && defined(GEMM_MM_RESHAPED_LHS_NT_RHS_T_TEXTURE)
#if defined(LHS_TRANSPOSE)
#define VTYPE(TYPE, SIZE) VEC_DATA_TYPE(TYPE, SIZE)
#if defined(MIXED_PRECISION)
#if(GPU_ARCH == GPU_ARCH_MIDGARD)
#define ARM_VFMA(N0, a, b, c) c += (CONVERT(a, VEC_DATA_TYPE(DATA_TYPE_ACCUMULATOR, N0))) * (CONVERT(b, VEC_DATA_TYPE(DATA_TYPE_ACCUMULATOR, N0)));
#else // GPU_ARCH == GPU_ARCH_MIDGARD
#define ARM_VFMA(N0, a, b, c) c = fma((CONVERT(a, VEC_DATA_TYPE(DATA_TYPE_ACCUMULATOR, N0))), (CONVERT(b, VEC_DATA_TYPE(DATA_TYPE_ACCUMULATOR, N0))), (c));
#endif // GPU_ARCH == GPU_ARCH_MIDGARD
#else // defined(MIXED_PRECISION
#if(GPU_ARCH == GPU_ARCH_MIDGARD)
#define ARM_VFMA(N0, a, b, c) c += (a) * (b);
#else // GPU_ARCH == GPU_ARCH_MIDGARD
#define ARM_VFMA(N0, a, b, c) c = fma((a), (b), (c));
#endif // GPU_ARCH == GPU_ARCH_MIDGARD
#endif // defined(MIXED_PRECISION)
#define ARM_VVM_T_NT_1xN0x1(N0, TYPE, a, b, C) \
({ \
ARM_VFMA(N0, (VTYPE(TYPE, N0))(a), b, (C##0)); \
})
#define ARM_VVM_T_NT_2xN0x1(N0, TYPE, a, b, C) \
({ \
ARM_VFMA(N0, (VTYPE(TYPE, N0))(a.s0), b, (C##0)); \
ARM_VFMA(N0, (VTYPE(TYPE, N0))(a.s1), b, (C##1)); \
})
#define ARM_VVM_T_NT_3xN0x1(N0, TYPE, a, b, C) \
({ \
ARM_VVM_T_NT_2xN0x1(N0, TYPE, a, b, C); \
ARM_VFMA(N0, (VTYPE(TYPE, N0))(a.s2), b, (C##2)); \
})
#define ARM_VVM_T_NT_4xN0x1(N0, TYPE, a, b, C) \
({ \
ARM_VVM_T_NT_3xN0x1(N0, TYPE, a, b, C); \
ARM_VFMA(N0, (VTYPE(TYPE, N0))(a.s3), b, (C##3)); \
})
#define ARM_VVM_T_NT_8xN0x1(N0, TYPE, a, b, C) \
({ \
ARM_VVM_T_NT_4xN0x1(N0, TYPE, a, b, C); \
ARM_VFMA(N0, (VTYPE(TYPE, N0))(a.s4), b, (C##4)); \
ARM_VFMA(N0, (VTYPE(TYPE, N0))(a.s5), b, (C##5)); \
ARM_VFMA(N0, (VTYPE(TYPE, N0))(a.s6), b, (C##6)); \
ARM_VFMA(N0, (VTYPE(TYPE, N0))(a.s7), b, (C##7)); \
})
// Factory macro for the column-vector (transposed) by row-vector (not transposed) multiplication. K0 = 1
// a is the column-vector (transposed)
// b is the row-vector (not transposed)
// C is the output matrix
// Lower case is a vector (a, b)
// Upper case is a matrix (C)
#define ARM_VVM_T_NT_M0xN0x1(M0, N0, TYPE, a, b, C) ARM_VVM_T_NT_##M0##xN0x1(N0, TYPE, a, b, C)
#define ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, A, B, C) \
({ \
ARM_VVM_T_NT_M0xN0x1(M0, N0, TYPE, (A##0), (B##0), C); \
})
#define ARM_MM_T_NT_M0xN0x2(M0, N0, TYPE, A, B, C) \
({ \
ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, A, B, C); \
ARM_VVM_T_NT_M0xN0x1(M0, N0, TYPE, (A##1), (B##1), C); \
})
#define ARM_MM_T_NT_M0xN0x3(M0, N0, TYPE, A, B, C) \
({ \
ARM_MM_T_NT_M0xN0x2(M0, N0, TYPE, A, B, C); \
ARM_VVM_T_NT_M0xN0x1(M0, N0, TYPE, (A##2), (B##2), C); \
})
#define ARM_MM_T_NT_M0xN0x4(M0, N0, TYPE, A, B, C) \
({ \
ARM_MM_T_NT_M0xN0x3(M0, N0, TYPE, A, B, C); \
ARM_VVM_T_NT_M0xN0x1(M0, N0, TYPE, (A##3), (B##3), C); \
})
#define ARM_MM_T_NT_M0xN0x8(M0, N0, TYPE, A, B, C) \
({ \
ARM_MM_T_NT_M0xN0x4(M0, N0, TYPE, A, B, C); \
ARM_VVM_T_NT_M0xN0x1(M0, N0, TYPE, (A##4), (B##4), C); \
ARM_VVM_T_NT_M0xN0x1(M0, N0, TYPE, (A##5), (B##5), C); \
ARM_VVM_T_NT_M0xN0x1(M0, N0, TYPE, (A##6), (B##6), C); \
ARM_VVM_T_NT_M0xN0x1(M0, N0, TYPE, (A##7), (B##7), C); \
})
#define ARM_MM_T_NT_M0xN0x16(M0, N0, TYPE, A, B, C) \
({ \
ARM_MM_T_NT_M0xN0x8(M0, N0, TYPE, A, B, C); \
ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, (A##8), (B##8), C); \
ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, (A##9), (B##9), C); \
ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, (A##A), (B##A), C); \
ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, (A##B), (B##B), C); \
ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, (A##C), (B##C), C); \
ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, (A##D), (B##D), C); \
ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, (A##E), (B##E), C); \
ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, (A##F), (B##F), C); \
})
// Factory macro for the matrix (transposed) by matrix (not transposed) multiplication.
// The dimensions for this matrix multiplications are defined through M0, N0 and K0
// The dimensions supported are:
// M0: 1, 2, 3, 4, 8
// N0: 1, 2, 3, 4, 8, 16
// K0: 1, 2, 3, 4, 8, 16
// This macro calls the vector-by-matrix macro K0 times
// A, B and C are matrices
#define ARM_MM_T_NT(M0, N0, K0, TYPE, A, B, C) \
CONCAT(ARM_MM_T_NT_M0xN0x, K0) \
(M0, N0, TYPE, A, B, C)
#if defined(GEMM_MM_RESHAPED_LHS_T_RHS_NT)
/** This OpenCL kernel computes the matrix multiplication between 2 matrices.
* The LHS matrix must be reshaped with @ref CLGEMMReshapeLHSMatrixKernel and the M0xK0 must be transposed
* The RHS matrix must be reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the K0xN0 must be NOT transposed
* @note This kernel is duplicated in /experimental/gemm_fused_post_ops/act_eltwise_op_act/gemm_mm_reshaped.cl
*
* @note LHS_TRANSPOSE should be passed at compile time in order to compile this OpenCL kernel (e.g. -DLHS_TRANSPOSE).
* @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time.
* @note The GEMM's dimensions M, N and K must be passed at compile time using -DM, -DN and -DK (e.g. -DM=52, -DN=90 and -DK=24).
* @note The block's dimensions used for reshaping the LHS matrix and the RHS matrix (M0, N0 and K0) must be passed at compile time using -DM0, -DN0 and -DK0 (e.g. -DM0=4, -DN0=8, -DK0=4).
* @note The number of M0xK0 vertical blocks stored on the same output row of the reshaped LHS matrix must be passed at compile time using -DV0 (e.g. -DV0=2)
* @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2)
* @note If the M0xK0 blocks in the reshaped LHS matrix have been interleaved, the option -DLHS_INTERLEAVE must passed at compile time.
* @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time.
* @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1)
* @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1)
* @note Only the following configurations of M0, N0 and K0 are currently supported:
* - M0 = 2, 3, 4, 8
* - N0 = 2, 3, 4, 8, 16
* - K0 = 2, 3, 4, 8, 16
* - V0 >= 1
* - H0 >= 1
*
* @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
* The activation function is performed after the bias addition
* @note In case the output has to be reinterpreted as a 3D tensor (e.g. output of convolution layer), the following information must be passed at compile time:
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
* -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor.
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix NOT reshaped
*
* @param[in] lhs_ptr Pointer to the LHS reshaped matrix. Supported data type: F16/F32
* @param[in] lhs_stride_x Stride of the LHS reshaped matrix in X dimension (in bytes)
* @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] lhs_stride_y Stride of the LHS reshaped matrix in Y dimension (in bytes)
* @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS reshaped matrix
* @param[in] rhs_ptr Pointer to the RHS reshaped matrix. Supported data type: same as @p lhs_ptr
* @param[in] rhs_stride_x Stride of the RHS reshaped matrix in X dimension (in bytes)
* @param[in] rhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] rhs_stride_y Stride of the RHS reshaped matrix in Y dimension (in bytes)
* @param[in] rhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS reshaped matrix
* @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
* @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
* @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] bias_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
* @param[in] bias_step_y (Optional) bias_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes)
* @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
* @param[in] lhs_stride_z Stride of the LHS reshaped matrix in Z dimension (in bytes)
* @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes)
* @param[in] bias_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] dst_cross_plane_pad (Optional) Bottom paddings in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
* @param[in] M Number of rows in LHS matrix not reshaped.
* @param[in] N Number of columns in RHS matrix not reshaped.
* @param[in] K Number of columns in LHS matrix and rows in RHS matrix not reshaped.
*/
__kernel void gemm_mm_reshaped_lhs_t_rhs_nt(IMAGE_DECLARATION(lhs),
IMAGE_DECLARATION(rhs),
#if defined(BETA)
IMAGE_DECLARATION(bias),
#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint lhs_stride_z,
uint rhs_stride_z,
#if defined(BETA)
uint bias_stride_z,
#endif //defined(BETA)
uint dst_stride_z
#if defined(REINTERPRET_OUTPUT_AS_3D)
,
uint dst_cross_plane_pad
#endif // REINTERPRET_OUTPUT_AS_3D
,
const int M,
const int N,
const int K)
{
// Block size
#define LHS_BLOCK_SIZE ((K0) * (M0))
#if defined(LHS_INTERLEAVE)
#define LHS_OFFSET_X (M0)
#define LHS_STEP_X ((M0) * (V0))
#define LHS_STEP_LOOP (1)
#else // defined(INTERLEAVE)
#define LHS_OFFSET_X (LHS_BLOCK_SIZE)
#define LHS_STEP_X (M0)
#define LHS_STEP_LOOP (V0)
#endif // defined(INTERLEAVE)
// Block size
#define RHS_BLOCK_SIZE ((K0) * (N0))
// RHS offset and step X
#if defined(RHS_INTERLEAVE)
#define RHS_OFFSET_X (N0)
#define RHS_STEP_X ((N0) * (H0))
#else // defined(RHS_INTERLEAVE)
#define RHS_OFFSET_X (RHS_BLOCK_SIZE)
#define RHS_STEP_X (N0)
#endif // defined(RHS_INTERLEAVE)
const uint x = get_global_id(0);
const uint y = get_global_id(1);
const uint z = get_global_id(2);
const bool cond_y = ((get_global_id(1) + 1) * M0 >= M);
const bool cond_x = ((get_global_id(0) + 1) * N0 >= N);
#if defined(DUMMY_WORK_ITEMS)
if((x * N0 >= N) || (y * M0 >= M))
{
return;
}
#endif // defined(DUMMY_WORK_ITEMS)
// Compute LHS matrix address
__global uchar *lhs_addr = lhs_ptr + lhs_offset_first_element_in_bytes + (y % V0) * (uint)LHS_OFFSET_X * sizeof(DATA_TYPE) + (y / V0) * (uint)lhs_stride_y + (z * lhs_stride_z);
// Compute RHS matrix address
__global uchar *rhs_addr = rhs_ptr + rhs_offset_first_element_in_bytes + (x % H0) * (uint)RHS_OFFSET_X * sizeof(DATA_TYPE) + (x / (uint)H0) * rhs_stride_y;
#if defined(MATRIX_B_DEPTH)
// Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
rhs_addr += (z % MATRIX_B_DEPTH) * rhs_stride_z;
#else // defined(MATRIX_B_DEPTH)
rhs_addr += z * rhs_stride_z;
#endif // defined(MATRIX_B_DEPTH)
// Initialize the accumulators
REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE_ACCUMULATOR, N0), c, 0);
REPEAT_VAR_INIT_TO_CONST(M0, uint, zero, 0);
__global DATA_TYPE *lhs = (__global DATA_TYPE *)(lhs_addr);
__global DATA_TYPE *rhs = (__global DATA_TYPE *)(rhs_addr);
for(int i = 0; i < K; i += K0)
{
VEC_DATA_TYPE(DATA_TYPE, M0)
a0;
VEC_DATA_TYPE(DATA_TYPE, N0)
b0;
a0 = VLOAD(M0)(0, lhs);
b0 = VLOAD(N0)(0, rhs);
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
rhs += RHS_STEP_X;
#if K0 > 1
a0 = VLOAD(M0)(0, lhs);
b0 = VLOAD(N0)(0, rhs);
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
rhs += RHS_STEP_X;
#endif // K0 > 1
#if K0 > 2
a0 = VLOAD(M0)(0, lhs);
b0 = VLOAD(N0)(0, rhs);
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
rhs += RHS_STEP_X;
#endif // K0 > 2
#if K0 > 3
a0 = VLOAD(M0)(0, lhs);
b0 = VLOAD(N0)(0, rhs);
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
rhs += RHS_STEP_X;
#endif // K0 > 3
#if K0 > 4
a0 = VLOAD(M0)(0, lhs);
b0 = VLOAD(N0)(0, rhs);
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
rhs += RHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = VLOAD(N0)(0, rhs);
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
rhs += RHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = VLOAD(N0)(0, rhs);
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
rhs += RHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = VLOAD(N0)(0, rhs);
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
rhs += RHS_STEP_X;
#endif // K0 > 4
#if K0 > 8
a0 = VLOAD(M0)(0, lhs);
b0 = VLOAD(N0)(0, rhs);
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
rhs += RHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = VLOAD(N0)(0, rhs);
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
rhs += RHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = VLOAD(N0)(0, rhs);
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
rhs += RHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = VLOAD(N0)(0, rhs);
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
rhs += RHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = VLOAD(N0)(0, rhs);
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
rhs += RHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = VLOAD(N0)(0, rhs);
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
rhs += RHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = VLOAD(N0)(0, rhs);
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
rhs += RHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = VLOAD(N0)(0, rhs);
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
rhs += RHS_STEP_X;
#endif // K0 > 8
#ifndef LHS_INTERLEAVE
lhs += (M0 * K0 * (V0 - 1));
#endif // LHS_INTERLEAVE
#ifndef RHS_INTERLEAVE
rhs += (N0 * K0 * (H0 - 1));
#endif // RHS_INTERLEAVE
}
__global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (y * (uint)M0 * dst_stride_y);
REPEAT_VAR_INIT_TO_CONST(M0, uint, zout, 0);
#if defined(REINTERPRET_OUTPUT_AS_3D)
// The plane (zin) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
CALCULATE_Z_OFFSET(M0, uint, zout, y * (uint)M0, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += z * dst_stride_z;
#endif // defined(REINTERPRET_OUTPUT_AS_3D)
// Multiply by the weight of matrix-matrix product and store the result
#if defined(ALPHA)
SCALE_BLOCK(M0, DATA_TYPE, c, ALPHA);
#endif // defined(ALPHA)
// Add beta*bias
#if defined(BETA)
#if defined(BROADCAST_BIAS)
__global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE));
LOAD_BLOCK_BOUNDARY_AWARE(1, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, 1, PARTIAL_STORE_N0, false, cond_x);
#ifndef UNIT_BETA
SCALE_BLOCK(1, DATA_TYPE, bias, BETA);
#endif // UNIT_BIAS
// c = c + bias[broadcasted]
#if defined(MIXED_PRECISION)
CONVERT_BLOCK(1, N0, DATA_TYPE_ACCUMULATOR, bias, bias_hp);
ADD_BLOCK_BROADCAST(M0, c, bias_hp0);
#else // defined(MIXED_PRECISION)
ADD_BLOCK_BROADCAST(M0, c, bias0);
#endif // defined(MIXED_PRECISION)
#else // defined(BROADCAST_BIAS)
__global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE)) + (get_global_id(1) * (uint)M0 * bias_stride_y) + get_global_id(
2) * bias_stride_z;
LOAD_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#ifndef UNIT_BETA
SCALE_BLOCK(M0, DATA_TYPE, bias, BETA);
#endif // UNIT_BIAS
#if defined(MIXED_PRECISION)
CONVERT_BLOCK(M0, N0, DATA_TYPE_ACCUMULATOR, bias, bias_hp);
ADD_BLOCK(M0, c, bias_hp);
#else // defined(MIXED_PRECISION)
ADD_BLOCK(M0, c, bias);
#endif // defined(MIXED_PRECISION)
#endif // defined(BROADCAST_BIAS)
#endif // defined(BETA)
#if defined(ACTIVATION_TYPE)
#if defined(MIXED_PRECISION)
ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE_ACCUMULATOR, VEC_SIZE, c, A_VAL, B_VAL);
#else // defined(MIXED_PRECISION)
ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE, VEC_SIZE, c, A_VAL, B_VAL);
#endif // defined(MIXED_PRECISION)
#endif // defined(ACTIVATION_TYPE)
// Store output block
#if defined(MIXED_PRECISION)
CONVERT_BLOCK(M0, N0, DATA_TYPE, c, c_lp);
STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c_lp, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#else // defined(MIXED_PRECISION)
STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#endif // defined(MIXED_PRECISION)
#undef LHS_BLOCK_SIZE
#undef LHS_OFFSET_X
#undef LHS_STEP_X
#undef RHS_BLOCK_SIZE
#undef RHS_OFFSET_X
#undef RHS_STEP_X
}
#endif // defined(GEMM_MM_RESHAPED_LHS_T_RHS_NT)
#if defined(OPENCL_IMAGE_SUPPORT) && defined(GEMM_MM_RESHAPED_LHS_T_RHS_NT_TEXTURE)
/** This OpenCL kernel computes the matrix multiplication between 2 matrices. The RHS matrix is stored in OpenCL image object.
* The LHS matrix must be reshaped with @ref CLGEMMReshapeLHSMatrixKernel and the M0xK0 must be transposed
* The RHS matrix must be reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the K0xN0 must be NOT transposed
* @note This kernel is duplicated in /experimental/gemm_fused_post_ops/act_eltwise_op_act/gemm_mm_reshaped.cl
*
* @note -DOPENCL_IMAGE_SUPPORT must be passed at compile time in order to compile this OpenCL kernel
* @note LHS_TRANSPOSE should be passed at compile time in order to compile this OpenCL kernel (e.g. -DLHS_TRANSPOSE).
* @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time.
* @note The GEMM's dimensions M, N and K must be passed at runtime.
* @note The height of the RHS matrix, defined before creating the OpenCL image object from the OpenCL buffer, should be passed at compile time using -DRHS_HEIGHT=<value> (e.g. -DRHS_HEIGHT=32)
* Since we cannot create a 3d image from a buffer, the third dimension could be collapsed with the second dimension so RHS_HEIGHT
* could be different from the value returned by get_image_height(rhs_img).
* @note The block's dimensions used for reshaping the LHS matrix and the RHS matrix (M0, N0 and K0) must be passed at compile time using -DM0, -DN0 and -DK0 (e.g. -DM0=4, -DN0=8, -DK0=4).
* @note The number of M0xK0 vertical blocks stored on the same output row of the reshaped LHS matrix must be passed at compile time using -DV0 (e.g. -DV0=2)
* @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2)
* @note If the M0xK0 blocks in the reshaped LHS matrix have been interleaved, the option -DLHS_INTERLEAVE must passed at compile time.
* @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time.
* @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1)
* @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1)
* @note Only the following configurations of M0, N0 and K0 are currently supported:
* - M0 = 2, 3, 4, 8
* - N0 = 4, 8, 16
* - K0 = 4, 8, 16
* - V0 >= 1
* - H0 >= 1
*
* @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
* The activation function is performed after the bias addition
* @note In case the output has to be reinterpreted as a 3D tensor (e.g. output of convolution layer), the following information must be passed at compile time:
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
* -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor.
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix NOT reshaped
*
* @param[in] lhs_ptr Pointer to the LHS reshaped matrix. Supported data type: F32
* @param[in] lhs_stride_x Stride of the LHS reshaped matrix in X dimension (in bytes)
* @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] lhs_stride_y Stride of the LHS reshaped matrix in Y dimension (in bytes)
* @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS reshaped matrix
* @param[in] rhs_img The RHS reshaped matrix as cl_image 2d. Supported data type: same as @p lhs_ptr
* @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
* @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
* @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] bias_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
* @param[in] bias_step_y (Optional) bias_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes)
* @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
* @param[in] lhs_stride_z Stride of the LHS reshaped matrix in Z dimension (in bytes)
* @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes)
* @param[in] bias_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] dst_cross_plane_pad (Optional) Bottom paddings in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
* @param[in] M Number of rows in LHS matrix not reshaped.
* @param[in] N Number of columns in RHS matrix not reshaped.
* @param[in] K Number of columns in LHS matrix and rows in RHS matrix not reshaped.
*/
__kernel void gemm_mm_reshaped_lhs_t_rhs_nt_texture(IMAGE_DECLARATION(lhs),
__read_only image2d_t rhs_img,
#if defined(BETA)
IMAGE_DECLARATION(bias),
#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint lhs_stride_z,
uint rhs_stride_z,
#if defined(BETA)
uint bias_stride_z,
#endif //defined(BETA)
uint dst_stride_z
#if defined(REINTERPRET_OUTPUT_AS_3D)
,
uint dst_cross_plane_pad
#endif // REINTERPRET_OUTPUT_AS_3D
,
const int M,
const int N,
const int K)
{
// Pixel unit
#define PIXEL_UNIT CONVERT_VECTOR_SIZE_TO_PIXEL_UNIT(N0)
// Block size
#define LHS_BLOCK_SIZE ((K0) * (M0))
#if defined(LHS_INTERLEAVE)
#define LHS_OFFSET_X (M0)
#define LHS_STEP_X ((M0) * (V0))
#define LHS_STEP_LOOP (1)
#else // defined(INTERLEAVE)
#define LHS_OFFSET_X (LHS_BLOCK_SIZE)
#define LHS_STEP_X (M0)
#define LHS_STEP_LOOP (V0)
#endif // defined(INTERLEAVE)
// Block size
#define RHS_BLOCK_SIZE ((K0) * (PIXEL_UNIT))
// RHS offset and step X
#if defined(RHS_INTERLEAVE)
#define RHS_OFFSET_X (PIXEL_UNIT)
#define RHS_STEP_X ((PIXEL_UNIT) * (H0))
#else // defined(RHS_INTERLEAVE)
#define RHS_OFFSET_X (RHS_BLOCK_SIZE)
#define RHS_STEP_X (PIXEL_UNIT)
#endif // defined(RHS_INTERLEAVE)
const uint x = get_global_id(0);
const uint y = get_global_id(1);
const uint z = get_global_id(2);
#if defined(DUMMY_WORK_ITEMS)
if((x * N0 >= N) || (y * M0 >= M))
{
return;
}
#endif // defined(DUMMY_WORK_ITEMS)
// Compute LHS matrix address
__global uchar *lhs_addr = lhs_ptr + lhs_offset_first_element_in_bytes + (y % V0) * (uint)LHS_OFFSET_X * sizeof(DATA_TYPE) + (y / V0) * (uint)lhs_stride_y + (z * lhs_stride_z);
#if defined(MATRIX_B_DEPTH)
// Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
const uint z_rhs = (z % MATRIX_B_DEPTH);
#else // defined(MATRIX_B_DEPTH)
const uint z_rhs = z;
#endif // defined(MATRIX_B_DEPTH)
// Compute RHS matrix coordinates
uint x_rhs = (x % H0) * (uint)RHS_OFFSET_X;
const uint y_rhs = (x / (uint)H0) + z_rhs * RHS_HEIGHT;
// Initialize the accumulators
REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE_ACCUMULATOR, N0), c, 0);
REPEAT_VAR_INIT_TO_CONST(M0, uint, zero, 0);
__global DATA_TYPE *lhs = (__global DATA_TYPE *)(lhs_addr);
for(int i = 0; i < K; i += K0)
{
VEC_DATA_TYPE(DATA_TYPE, M0)
a0;
VEC_DATA_TYPE(DATA_TYPE, N0)
b0;
a0 = VLOAD(M0)(0, lhs);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 0 * RHS_STEP_X), (y_rhs));
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
#if K0 > 1
a0 = VLOAD(M0)(0, lhs);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 1 * RHS_STEP_X), (y_rhs));
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
#endif // K0 > 1
#if K0 > 2
a0 = VLOAD(M0)(0, lhs);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 2 * RHS_STEP_X), (y_rhs));
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
#endif // K0 > 2
#if K0 > 3
a0 = VLOAD(M0)(0, lhs);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 3 * RHS_STEP_X), (y_rhs));
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
#endif // K0 > 3
#if K0 > 4
a0 = VLOAD(M0)(0, lhs);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 4 * RHS_STEP_X), (y_rhs));
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 5 * RHS_STEP_X), (y_rhs));
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 6 * RHS_STEP_X), (y_rhs));
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 7 * RHS_STEP_X), (y_rhs));
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
#endif // K0 > 4
#if K0 > 8
a0 = VLOAD(M0)(0, lhs);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 8 * RHS_STEP_X), (y_rhs));
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 9 * RHS_STEP_X), (y_rhs));
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 10 * RHS_STEP_X), (y_rhs));
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 11 * RHS_STEP_X), (y_rhs));
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 12 * RHS_STEP_X), (y_rhs));
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 13 * RHS_STEP_X), (y_rhs));
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 14 * RHS_STEP_X), (y_rhs));
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
a0 = VLOAD(M0)(0, lhs);
b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 15 * RHS_STEP_X), (y_rhs));
ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c);
lhs += LHS_STEP_X;
#endif // K0 > 8
#ifndef LHS_INTERLEAVE
lhs += (M0 * K0 * (V0 - 1));
#endif // LHS_INTERLEAVE
x_rhs += K0 * RHS_STEP_X;
#ifndef RHS_INTERLEAVE
x_rhs += (PIXEL_UNIT * K0 * (H0 - 1));
#endif // RHS_INTERLEAVE
}
__global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (y * (uint)M0 * dst_stride_y);
REPEAT_VAR_INIT_TO_CONST(M0, uint, zout, 0);
const bool cond_y = ((get_global_id(1) + 1) * M0 >= M);
const bool cond_x = ((get_global_id(0) + 1) * N0 >= N);
#if defined(REINTERPRET_OUTPUT_AS_3D)
// The plane (zin) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
CALCULATE_Z_OFFSET(M0, uint, zout, y * (uint)M0, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += z * dst_stride_z;
#endif // defined(REINTERPRET_OUTPUT_AS_3D)
// Multiply by the weight of matrix-matrix product and store the result
#if defined(ALPHA)
SCALE_BLOCK(M0, DATA_TYPE, c, ALPHA);
#endif // defined(ALPHA)
// Add beta*bias
#if defined(BETA)
#if defined(BROADCAST_BIAS)
__global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE));
LOAD_BLOCK_BOUNDARY_AWARE(1, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, 1, PARTIAL_STORE_N0, false, cond_x);
#ifndef UNIT_BETA
SCALE_BLOCK(1, DATA_TYPE, bias, BETA);
#endif // UNIT_BIAS
// c = c + bias[broadcasted]
#if defined(MIXED_PRECISION)
CONVERT_BLOCK(1, N0, DATA_TYPE_ACCUMULATOR, bias, bias_hp);
ADD_BLOCK_BROADCAST(M0, c, bias_hp0);
#else // defined(MIXED_PRECISION)
ADD_BLOCK_BROADCAST(M0, c, bias0);
#endif // defined(MIXED_PRECISION)
#else // defined(BROADCAST_BIAS)
__global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (y * (uint)M0 * bias_stride_y) + z * bias_stride_z;
LOAD_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#ifndef UNIT_BETA
SCALE_BLOCK(M0, DATA_TYPE, bias, BETA);
#endif // UNIT_BIAS
#if defined(MIXED_PRECISION)
CONVERT_BLOCK(M0, N0, DATA_TYPE_ACCUMULATOR, bias, bias_hp);
ADD_BLOCK(M0, c, bias_hp);
#else // defined(MIXED_PRECISION)
ADD_BLOCK(M0, c, bias);
#endif // defined(MIXED_PRECISION)
#endif // defined(BROADCAST_BIAS)
#endif // defined(BETA)
#if defined(ACTIVATION_TYPE)
#if defined(MIXED_PRECISION)
ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE_ACCUMULATOR, VEC_SIZE, c, A_VAL, B_VAL);
#else // defined(MIXED_PRECISION)
ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE, VEC_SIZE, c, A_VAL, B_VAL);
#endif // defined(MIXED_PRECISION)
#endif // defined(ACTIVATION_TYPE)
// Store output block
#if defined(MIXED_PRECISION)
CONVERT_BLOCK(M0, N0, DATA_TYPE, c, c_lp);
STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c_lp, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#else // defined(MIXED_PRECISION)
STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
#endif // defined(MIXED_PRECISION)
#undef LHS_BLOCK_SIZE
#undef LHS_OFFSET_X
#undef LHS_STEP_X
#undef RHS_BLOCK_SIZE
#undef RHS_OFFSET_X
#undef RHS_STEP_X
#undef PIXEL_UNIT
#undef LHS_STEP_LOOP
#undef RHS_STEP_LOOP
}
#endif // defined(OPENCL_IMAGE_SUPPORT) && defined(GEMM_MM_RESHAPED_LHS_T_RHS_NT_TEXTURE)
#endif // defined(LHS_TRANSPOSE)
#endif // defined(M0) && defined(N0) && defined(K0) && defined(V0) && defined(H0) && defined(DATA_TYPE) && defined(DATA_TYPE_ACCUMULATOR)
#if defined(M0) && defined(N0) && defined(K0) && defined(DATA_TYPE)
#define VFMA(a, b, c) \
({ \
c = fma(a, b, c); \
})
#if M0 == 1
#define RHS_VFMA_M0xN0(i, a, b, c) \
({ \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \
})
#elif M0 == 2 // M0 == 2
#define RHS_VFMA_M0xN0(i, a, b, c) \
({ \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \
})
#elif M0 == 3 // M0 == 3
#define RHS_VFMA_M0xN0(i, a, b, c) \
({ \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \
})
#elif M0 == 4 // M0 == 4
#define RHS_VFMA_M0xN0(i, a, b, c) \
({ \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \
})
#elif M0 == 5 // M0 == 5
#define RHS_VFMA_M0xN0(i, a, b, c) \
({ \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \
})
#elif M0 == 6 // M0 == 6
#define RHS_VFMA_M0xN0(i, a, b, c) \
({ \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##5).s##i), b, (c##5)); \
})
#elif M0 == 7 // M0 == 7
#define RHS_VFMA_M0xN0(i, a, b, c) \
({ \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##5).s##i), b, (c##5)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##6).s##i), b, (c##6)); \
})
#elif M0 == 8 // M0 == 8
#define RHS_VFMA_M0xN0(i, a, b, c) \
({ \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##5).s##i), b, (c##5)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##6).s##i), b, (c##6)); \
VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##7).s##i), b, (c##7)); \
})
#else // M0 not supported
#error "M0 not supported"
#endif // M0 not supported
#if defined(GEMM_MM_NATIVE)
/** This OpenCL kernel computes the matrix multiplication between 2 matrices.
* The LHS matrix is NOT reshaped
* The RHS matrix is NOT reshaped
* @note This kernel is duplicated in /experimental/gemm_fused_post_ops/act_eltwise_op_act/gemm_mm_native.cl
*
* @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time.
* @note The GEMM's dimensions (M,N and K) must be passed at runtime as kernel parameters.
* @note The number of M0 rows to process must be passed at compile time using -DM0 (e.g. -DM0=2)
* @note The number of K0 partial accumulations must be passed at compile time using -DK0 (e.g., -DK0=2)
* @note The number of N0 columns to process must be passed at compile time using -DN0 (e.g. -DN0=2)
* @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1)
* @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1)
* @note Only the following configurations of M0, N0 and K0 are currently supported:
* - M0 = 1, 2, 3, 4, 5, 6, 7, 8
* - N0 = 2, 3, 4, 8, 16
* - K0 = 2, 3, 4, 8, 16
*
* @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
* The activation function is performed after the bias addition
* @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time:
* -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
* -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor.
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix
*
* @param[in] lhs_ptr Pointer to the LHS matrix. Supported data type: F16/F32
* @param[in] lhs_stride_x Stride of the LHS matrix in X dimension (in bytes)
* @param[in] lhs_step_x lhs_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] lhs_stride_y Stride of the LHS matrix in Y dimension (in bytes)
* @param[in] lhs_step_y lhs_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS matrix
* @param[in] rhs_ptr Pointer to the RHS matrix. Supported data type: same as @p lhs_ptr
* @param[in] rhs_stride_x Stride of the RHS matrix in X dimension (in bytes)
* @param[in] rhs_step_x rhs_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] rhs_stride_y Stride of the RHS matrix in Y dimension (in bytes)
* @param[in] rhs_step_y rhs_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS matrix
* @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
* @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
* @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] bias_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
* @param[in] bias_step_y (Optional) bias_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes)
* @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
* @param[in] lhs_stride_z Stride of the LHS matrix in Z dimension (in bytes)
* @param[in] rhs_stride_z Stride of the RHS matrix in Z dimension (in bytes)
* @param[in] bias_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] M Number of rows in LHS matrix not reshaped.
* @param[in] N Number of columns in RHS matrix not reshaped.
* @param[in] K Number of columns in LHS matrix and rows in RHS matrix not reshaped.
* @param[in] lhs_cross_plane_pad (Optional) Bottom paddings for LHS matrix in unit of elements (only if defined REINTERPRET_INPUT_AS_3D)
* @param[in] dst_cross_plane_pad (Optional) Bottom paddings for the output matrix in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
*/
__kernel void gemm_mm_native(IMAGE_DECLARATION(lhs),
IMAGE_DECLARATION(rhs),
#if defined(BETA)
IMAGE_DECLARATION(bias),
#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint lhs_stride_z,
uint rhs_stride_z,
#if defined(BETA)
uint bias_stride_z,
#endif //defined(BETA)
uint dst_stride_z,
const int M,
const int N,
const int K
#if defined(REINTERPRET_INPUT_AS_3D)
,
uint lhs_cross_plane_pad
#endif // REINTERPRET_INPUT_AS_3D
#if defined(REINTERPRET_OUTPUT_AS_3D)
,
uint dst_cross_plane_pad
#endif // REINTERPRET_OUTPUT_AS_3D
)
{
// Block size
#define RHS_BLOCK_SIZE ((K0) * (N0))
// RHS offset and step X
#define RHS_OFFSET_X (RHS_BLOCK_SIZE)
uint x = get_global_id(0);
uint y = get_global_id(1);
uint z = get_global_id(2);
#if defined(DUMMY_WORK_ITEMS)
if((x * N0 >= N) || (y * M0 >= M))
{
return;
}
#endif // defined(DUMMY_WORK_ITEMS)
// Compute LHS matrix address
uint lhs_offset = lhs_offset_first_element_in_bytes + COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * (uint)lhs_stride_y;
// Compute RHS matrix address
uint rhs_offset = rhs_offset_first_element_in_bytes + x * N0 * sizeof(DATA_TYPE);
#if defined(MATRIX_B_DEPTH)
// Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
rhs_offset += (z % MATRIX_B_DEPTH) * rhs_stride_z;
#else // defined(MATRIX_B_DEPTH)
rhs_offset += z * rhs_stride_z;
#endif // defined(MATRIX_B_DEPTH)
REPEAT_VAR_INIT_TO_CONST(M0, uint, zlhs, 0);
REPEAT_VAR_INIT_TO_CONST(16, uint, zero, 0);
#if defined(REINTERPRET_INPUT_AS_3D)
// The plane (zlhs) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
CALCULATE_Z_OFFSET(M0, uint, zlhs, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply lhs_stride_z by DEPTH_GEMM3D
lhs_offset += z * lhs_stride_z * DEPTH_GEMM3D;
#else // defined(REINTERPRET_INPUT_AS_3D)
// Add offset for batched GEMM
lhs_offset += z * lhs_stride_z;
#endif // defined(REINTERPRET_INPUT_AS_3D)
// Initialize the accumulators
REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE, N0), c, 0); //VEC_DATA_TYPE(DATA_TYPE, N0) c0=0,c1=0,c2=0,... c(M0-1)=0;
int i = 0;
#if K0 > 1
for(; i <= (K - K0); i += K0)
{
// Supported cases (M0, K0):
// 1,2 - 1,3 - 1,4 - 1,8 - 1,16
// 2,2 - 2,3 - 2,4 - 2,8 - 2,16
// 3,2 - 3,3 - 3,4 - 3,8 - 3,16
// 4,2 - 4,3 - 4,4 - 4,8 - 4,16
// 5,2 - 5,3 - 5,4 - 5,8 - 5,16
// 6,2 - 6,3 - 6,4 - 6,8 - 6,16
// 7,2 - 7,3 - 7,4 - 7,8 - 7,16
// 8,2 - 8,3 - 8,4 - 8,8 - 8,16
// Load values from LHS matrix
LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zlhs);
// Load values from RHS matrix
LOAD_BLOCK(K0, N0, DATA_TYPE, b, rhs_ptr, rhs_offset, rhs_stride_y, zero);
RHS_VFMA_M0xN0(0, a, b0, c);
RHS_VFMA_M0xN0(1, a, b1, c);
#if K0 > 2
RHS_VFMA_M0xN0(2, a, b2, c);
#endif // K0 > 2
#if K0 > 3
RHS_VFMA_M0xN0(3, a, b3, c);
#endif // K0 > 3
#if K0 > 4
RHS_VFMA_M0xN0(4, a, b4, c);
RHS_VFMA_M0xN0(5, a, b5, c);
RHS_VFMA_M0xN0(6, a, b6, c);
RHS_VFMA_M0xN0(7, a, b7, c);
#endif // K0 > 4
#if K0 > 8
RHS_VFMA_M0xN0(8, a, b8, c);
RHS_VFMA_M0xN0(9, a, b9, c);
RHS_VFMA_M0xN0(A, a, bA, c);
RHS_VFMA_M0xN0(B, a, bB, c);
RHS_VFMA_M0xN0(C, a, bC, c);
RHS_VFMA_M0xN0(D, a, bD, c);
RHS_VFMA_M0xN0(E, a, bE, c);
RHS_VFMA_M0xN0(F, a, bF, c);
#endif // K0 > 8
lhs_offset += K0 * sizeof(DATA_TYPE);
rhs_offset += K0 * rhs_stride_y;
}
#endif // K0 > 1
// Left-over accumulations
for(; i < K; ++i)
{
// Load values from LHS matrix
VEC_DATA_TYPE(DATA_TYPE, 2)
a0 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 0 * lhs_stride_y + zlhs0));
#if M0 > 1
VEC_DATA_TYPE(DATA_TYPE, 2)
a1 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 1 * lhs_stride_y + zlhs1));
#endif // M0 > 1
#if M0 > 2
VEC_DATA_TYPE(DATA_TYPE, 2)
a2 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 2 * lhs_stride_y + zlhs2));
#endif // M0 > 2
#if M0 > 3
VEC_DATA_TYPE(DATA_TYPE, 2)
a3 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 3 * lhs_stride_y + zlhs3));
#endif // M0 > 3
#if M0 > 4
VEC_DATA_TYPE(DATA_TYPE, 2)
a4 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 4 * lhs_stride_y + zlhs4));
#endif // M0 > 4
#if M0 > 5
VEC_DATA_TYPE(DATA_TYPE, 2)
a5 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 5 * lhs_stride_y + zlhs5));
#endif // M0 > 5
#if M0 > 6
VEC_DATA_TYPE(DATA_TYPE, 2)
a6 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 6 * lhs_stride_y + zlhs6));
#endif // M0 > 6
#if M0 > 7
VEC_DATA_TYPE(DATA_TYPE, 2)
a7 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 7 * lhs_stride_y + zlhs7));
#endif // M0 > 7
VEC_DATA_TYPE(DATA_TYPE, N0)
b = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 0 * rhs_stride_y));
RHS_VFMA_M0xN0(0, a, b, c);
lhs_offset += sizeof(DATA_TYPE);
rhs_offset += rhs_stride_y;
}
__global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * dst_stride_y);
REPEAT_VAR_INIT_TO_CONST(M0, uint, zout, 0);
#if defined(REINTERPRET_OUTPUT_AS_3D)
// The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += z * dst_stride_z;
#endif // defined(REINTERPRET_OUTPUT_AS_3D)
// Multiply by the weight of matrix-matrix product and store the result
#if defined(ALPHA)
SCALE_BLOCK(M0, DATA_TYPE, c, ALPHA);
#endif // defined(ALPHA)
// Add beta*bias
#if defined(BETA)
#if defined(BROADCAST_BIAS)
__global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE));
LOAD_BLOCK(1, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero);
#ifndef UNIT_BETA
SCALE_BLOCK(1, DATA_TYPE, bias, BETA);
#endif // UNIT_BIAS
// c = c + bias[broadcasted]
ADD_BLOCK_BROADCAST(M0, c, bias0);
#else // defined(BROADCAST_BIAS)
__global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * bias_stride_y) + z * bias_stride_z;
LOAD_BLOCK(M0, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero);
#ifndef UNIT_BETA
SCALE_BLOCK(M0, DATA_TYPE, bias, BETA);
#endif // UNIT_BIAS
// c = c + bias
ADD_BLOCK(M0, c, bias);
#endif // defined(BROADCAST_BIAS)
#endif // defined(BETA)
#if defined(ACTIVATION_TYPE)
ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE, VEC_SIZE, c, A_VAL, B_VAL);
#endif // defined(ACTIVATION_TYPE)
const bool cond_y = y == 0;
const bool cond_x = ((x + 1) * N0 >= N);
// Store output block
STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
}
#endif // defined(GEMM_MM_NATIVE)
#endif // defined(M0) && defined(N0) && defined(K0) && defined(DATA_TYPE)
#if defined(BETA)
/** This OpenCL kernel performs the in-place matrix addition between 2 matrices taking into account that the second matrix might be weighted by a scalar value beta:
*
* @note The beta's value need to be passed at compile time using -DBETA
*
* @param[in] src_ptr Pointer to the source matrix. Supported data types: F32
* @param[in] src_stride_x Stride of the source matrix in X dimension (in bytes)
* @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] src_stride_y Stride of the source matrix in Y dimension (in bytes)
* @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] src_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] src_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes)
* @param[in] src_offset_first_element_in_bytes The offset of the first element in the source matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data types: same as @p src_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_gx_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes)
* @param[in] dst_step_y dst_gx_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] dst_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
*/
__kernel void gemm_ma_f32(TENSOR3D_DECLARATION(src),
TENSOR3D_DECLARATION(dst))
{
// Compute source and destination addresses
Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src);
Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst);
// Load values from A x B
float4 alpha_ab = vload4(0, (__global float *)dst.ptr);
// Load values from Matrix C
float4 c = vload4(0, (__global float *)src.ptr);
// Computes alpha * axb + beta * c
float4 out = alpha_ab + (float4)BETA * c;
// Store final result in axb matrix
vstore4(out, 0, (__global float *)dst.ptr);
}
#if defined(ARM_COMPUTE_OPENCL_FP16_ENABLED)
/** This OpenCL kernel performs the in-place matrix addition between 2 matrices taking into account that the second matrix might be weighted by a scalar value beta:
*
* @note The beta's value need to be passed at compile time using -DBETA
*
* @param[in] src_ptr Pointer to the source matrix. Supported data types: F16
* @param[in] src_stride_x Stride of the source matrix in X dimension (in bytes)
* @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] src_stride_y Stride of the source matrix in Y dimension (in bytes)
* @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] src_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] src_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes)
* @param[in] src_offset_first_element_in_bytes The offset of the first element in the source matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data types: same as @p src_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_gx_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes)
* @param[in] dst_step_y dst_gx_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] dst_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
*/
__kernel void gemm_ma_f16(TENSOR3D_DECLARATION(src),
TENSOR3D_DECLARATION(dst))
{
// Compute source and destination addresses
Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src);
Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst);
// Load values from A x B
half8 alpha_ab = vload8(0, (__global half *)dst.ptr);
// Load values from Matrix C
half8 c = vload8(0, (__global half *)src.ptr);
// Computes alpha * axb + beta * c
half8 out = alpha_ab + (half8)BETA * c;
// Store final result in axb matrix
vstore8(out, 0, (__global half *)dst.ptr);
}
#endif // defined(ARM_COMPUTE_OPENCL_FP16_ENABLED)
#endif // defined(BETA)