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/* ----------------------------------------------------------------------
* Copyright (C) 2010 ARM Limited. All rights reserved.
*
* $Date: 15. July 2011
* $Revision: V1.0.10
*
* Project: CMSIS DSP Library
* Title: arm_mat_mult_fast_q15.c
*
* Description: Q15 matrix multiplication (fast variant)
*
* Target Processor: Cortex-M4/Cortex-M3
*
* Version 1.0.10 2011/7/15
* Big Endian support added and Merged M0 and M3/M4 Source code.
*
* Version 1.0.3 2010/11/29
* Re-organized the CMSIS folders and updated documentation.
*
* Version 1.0.2 2010/11/11
* Documentation updated.
*
* Version 1.0.1 2010/10/05
* Production release and review comments incorporated.
*
* Version 1.0.0 2010/09/20
* Production release and review comments incorporated.
* -------------------------------------------------------------------- */
#include "arm_math.h"
/**
* @ingroup groupMatrix
*/
/**
* @addtogroup MatrixMult
* @{
*/
/**
* @brief Q15 matrix multiplication (fast variant) for Cortex-M3 and Cortex-M4
* @param[in] *pSrcA points to the first input matrix structure
* @param[in] *pSrcB points to the second input matrix structure
* @param[out] *pDst points to output matrix structure
* @param[in] *pState points to the array for storing intermediate results
* @return The function returns either
* <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
*
* @details
* <b>Scaling and Overflow Behavior:</b>
*
* \par
* The difference between the function arm_mat_mult_q15() and this fast variant is that
* the fast variant use a 32-bit rather than a 64-bit accumulator.
* The result of each 1.15 x 1.15 multiplication is truncated to
* 2.30 format. These intermediate results are accumulated in a 32-bit register in 2.30
* format. Finally, the accumulator is saturated and converted to a 1.15 result.
*
* \par
* The fast version has the same overflow behavior as the standard version but provides
* less precision since it discards the low 16 bits of each multiplication result.
* In order to avoid overflows completely the input signals must be scaled down.
* Scale down one of the input matrices by log2(numColsA) bits to
* avoid overflows, as a total of numColsA additions are computed internally for each
* output element.
*
* \par
* See <code>arm_mat_mult_q15()</code> for a slower implementation of this function
* which uses 64-bit accumulation to provide higher precision.
*/
arm_status arm_mat_mult_fast_q15(
const arm_matrix_instance_q15 * pSrcA,
const arm_matrix_instance_q15 * pSrcB,
arm_matrix_instance_q15 * pDst,
q15_t * pState)
{
q31_t sum; /* accumulator */
q31_t in; /* Temporary variable to hold the input value */
q15_t *pSrcBT = pState; /* input data matrix pointer for transpose */
q15_t *pInA = pSrcA->pData; /* input data matrix pointer A of Q15 type */
q15_t *pInB = pSrcB->pData; /* input data matrix pointer B of Q15 type */
// q15_t *pDst = pDst->pData; /* output data matrix pointer */
q15_t *px; /* Temporary output data matrix pointer */
uint16_t numRowsA = pSrcA->numRows; /* number of rows of input matrix A */
uint16_t numColsB = pSrcB->numCols; /* number of columns of input matrix B */
uint16_t numColsA = pSrcA->numCols; /* number of columns of input matrix A */
uint16_t numRowsB = pSrcB->numRows; /* number of rows of input matrix A */
uint16_t col, i = 0u, row = numRowsB, colCnt; /* loop counters */
arm_status status; /* status of matrix multiplication */
#ifdef ARM_MATH_MATRIX_CHECK
/* Check for matrix mismatch condition */
if((pSrcA->numCols != pSrcB->numRows) ||
(pSrcA->numRows != pDst->numRows) || (pSrcB->numCols != pDst->numCols))
{
/* Set status as ARM_MATH_SIZE_MISMATCH */
status = ARM_MATH_SIZE_MISMATCH;
}
else
#endif /* #ifdef ARM_MATH_MATRIX_CHECK */
{
/* Matrix transpose */
do
{
/* Apply loop unrolling and exchange the columns with row elements */
col = numColsB >> 2;
/* The pointer px is set to starting address of the column being processed */
px = pSrcBT + i;
/* First part of the processing with loop unrolling. Compute 4 outputs at a time.
** a second loop below computes the remaining 1 to 3 samples. */
while(col > 0u)
{
/* Read two elements from the row */
in = *__SIMD32(pInB)++;
/* Unpack and store one element in the destination */
#ifndef ARM_MATH_BIG_ENDIAN
*px = (q15_t) in;
#else
*px = (q15_t) ((in & (q31_t) 0xffff0000) >> 16);
#endif /* #ifndef ARM_MATH_BIG_ENDIAN */
/* Update the pointer px to point to the next row of the transposed matrix */
px += numRowsB;
/* Unpack and store the second element in the destination */
#ifndef ARM_MATH_BIG_ENDIAN
*px = (q15_t) ((in & (q31_t) 0xffff0000) >> 16);
#else
*px = (q15_t) in;
#endif /* #ifndef ARM_MATH_BIG_ENDIAN */
/* Update the pointer px to point to the next row of the transposed matrix */
px += numRowsB;
/* Read two elements from the row */
in = *__SIMD32(pInB)++;
/* Unpack and store one element in the destination */
#ifndef ARM_MATH_BIG_ENDIAN
*px = (q15_t) in;
#else
*px = (q15_t) ((in & (q31_t) 0xffff0000) >> 16);
#endif /* #ifndef ARM_MATH_BIG_ENDIAN */
/* Update the pointer px to point to the next row of the transposed matrix */
px += numRowsB;
/* Unpack and store the second element in the destination */
#ifndef ARM_MATH_BIG_ENDIAN
*px = (q15_t) ((in & (q31_t) 0xffff0000) >> 16);
#else
*px = (q15_t) in;
#endif /* #ifndef ARM_MATH_BIG_ENDIAN */
/* Update the pointer px to point to the next row of the transposed matrix */
px += numRowsB;
/* Decrement the column loop counter */
col--;
}
/* If the columns of pSrcB is not a multiple of 4, compute any remaining output samples here.
** No loop unrolling is used. */
col = numColsB % 0x4u;
while(col > 0u)
{
/* Read and store the input element in the destination */
*px = *pInB++;
/* Update the pointer px to point to the next row of the transposed matrix */
px += numRowsB;
/* Decrement the column loop counter */
col--;
}
i++;
/* Decrement the row loop counter */
row--;
} while(row > 0u);
/* Reset the variables for the usage in the following multiplication process */
row = numRowsA;
i = 0u;
px = pDst->pData;
/* The following loop performs the dot-product of each row in pSrcA with each column in pSrcB */
/* row loop */
do
{
/* For every row wise process, the column loop counter is to be initiated */
col = numColsB;
/* For every row wise process, the pIn2 pointer is set
** to the starting address of the transposed pSrcB data */
pInB = pSrcBT;
/* column loop */
do
{
/* Set the variable sum, that acts as accumulator, to zero */
sum = 0;
/* Apply loop unrolling and compute 2 MACs simultaneously. */
colCnt = numColsA >> 1;
/* Initiate the pointer pIn1 to point to the starting address of the column being processed */
pInA = pSrcA->pData + i;
/* matrix multiplication */
while(colCnt > 0u)
{
/* c(m,n) = a(1,1)*b(1,1) + a(1,2) * b(2,1) + .... + a(m,p)*b(p,n) */
sum = __SMLAD(*__SIMD32(pInA)++, *__SIMD32(pInB)++, sum);
/* Decrement the loop counter */
colCnt--;
}
/* process odd column samples */
if((numColsA & 0x1u) > 0u)
{
/* c(m,n) = a(1,1)*b(1,1) + a(1,2) * b(2,1) + .... + a(m,p)*b(p,n) */
sum += ((q31_t) * pInA * (*pInB++));
}
/* Saturate and store the result in the destination buffer */
*px = (q15_t) (sum >> 15);
px++;
/* Decrement the column loop counter */
col--;
} while(col > 0u);
i = i + numColsA;
/* Decrement the row loop counter */
row--;
} while(row > 0u);
/* set status as ARM_MATH_SUCCESS */
status = ARM_MATH_SUCCESS;
}
/* Return to application */
return (status);
}
/**
* @} end of MatrixMult group
*/