| // |
| // Copyright (c) 2017 The Khronos Group Inc. |
| // |
| // Licensed under the Apache License, Version 2.0 (the "License"); |
| // you may not use this file except in compliance with the License. |
| // You may obtain a copy of the License at |
| // |
| // http://www.apache.org/licenses/LICENSE-2.0 |
| // |
| // Unless required by applicable law or agreed to in writing, software |
| // distributed under the License is distributed on an "AS IS" BASIS, |
| // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| // See the License for the specific language governing permissions and |
| // limitations under the License. |
| // |
| |
| #include "common.h" |
| #include "function_list.h" |
| #include "test_functions.h" |
| #include "utility.h" |
| |
| #include <cstring> |
| |
| namespace { |
| |
| int BuildKernel(const char *name, int vectorSize, cl_uint kernel_count, |
| cl_kernel *k, cl_program *p, bool relaxedMode) |
| { |
| const char *c[] = { "#pragma OPENCL EXTENSION cl_khr_fp64 : enable\n", |
| "__kernel void math_kernel", |
| sizeNames[vectorSize], |
| "( __global double", |
| sizeNames[vectorSize], |
| "* out, __global double", |
| sizeNames[vectorSize], |
| "* in )\n" |
| "{\n" |
| " size_t i = get_global_id(0);\n" |
| " out[i] = ", |
| name, |
| "( in[i] );\n" |
| "}\n" }; |
| |
| const char *c3[] = { |
| "#pragma OPENCL EXTENSION cl_khr_fp64 : enable\n", |
| "__kernel void math_kernel", |
| sizeNames[vectorSize], |
| "( __global double* out, __global double* in)\n" |
| "{\n" |
| " size_t i = get_global_id(0);\n" |
| " if( i + 1 < get_global_size(0) )\n" |
| " {\n" |
| " double3 f0 = vload3( 0, in + 3 * i );\n" |
| " f0 = ", |
| name, |
| "( f0 );\n" |
| " vstore3( f0, 0, out + 3*i );\n" |
| " }\n" |
| " else\n" |
| " {\n" |
| " size_t parity = i & 1; // Figure out how many elements are " |
| "left over after BUFFER_SIZE % (3*sizeof(float)). Assume power of two " |
| "buffer size \n" |
| " double3 f0;\n" |
| " switch( parity )\n" |
| " {\n" |
| " case 1:\n" |
| " f0 = (double3)( in[3*i], NAN, NAN ); \n" |
| " break;\n" |
| " case 0:\n" |
| " f0 = (double3)( in[3*i], in[3*i+1], NAN ); \n" |
| " break;\n" |
| " }\n" |
| " f0 = ", |
| name, |
| "( f0 );\n" |
| " switch( parity )\n" |
| " {\n" |
| " case 0:\n" |
| " out[3*i+1] = f0.y; \n" |
| " // fall through\n" |
| " case 1:\n" |
| " out[3*i] = f0.x; \n" |
| " break;\n" |
| " }\n" |
| " }\n" |
| "}\n" |
| }; |
| |
| const char **kern = c; |
| size_t kernSize = sizeof(c) / sizeof(c[0]); |
| |
| if (sizeValues[vectorSize] == 3) |
| { |
| kern = c3; |
| kernSize = sizeof(c3) / sizeof(c3[0]); |
| } |
| |
| char testName[32]; |
| snprintf(testName, sizeof(testName) - 1, "math_kernel%s", |
| sizeNames[vectorSize]); |
| |
| return MakeKernels(kern, (cl_uint)kernSize, testName, kernel_count, k, p, |
| relaxedMode); |
| } |
| |
| struct BuildKernelInfo |
| { |
| cl_uint offset; // the first vector size to build |
| cl_uint kernel_count; |
| KernelMatrix &kernels; |
| cl_program *programs; |
| const char *nameInCode; |
| bool relaxedMode; // Whether to build with -cl-fast-relaxed-math. |
| }; |
| |
| cl_int BuildKernelFn(cl_uint job_id, cl_uint thread_id UNUSED, void *p) |
| { |
| BuildKernelInfo *info = (BuildKernelInfo *)p; |
| cl_uint i = info->offset + job_id; |
| return BuildKernel(info->nameInCode, i, info->kernel_count, |
| info->kernels[i].data(), info->programs + i, |
| info->relaxedMode); |
| } |
| |
| // Thread specific data for a worker thread |
| struct ThreadInfo |
| { |
| cl_mem inBuf; // input buffer for the thread |
| cl_mem outBuf[VECTOR_SIZE_COUNT]; // output buffers for the thread |
| float maxError; // max error value. Init to 0. |
| double maxErrorValue; // position of the max error value. Init to 0. |
| cl_command_queue tQueue; // per thread command queue to improve performance |
| }; |
| |
| struct TestInfo |
| { |
| size_t subBufferSize; // Size of the sub-buffer in elements |
| const Func *f; // A pointer to the function info |
| cl_program programs[VECTOR_SIZE_COUNT]; // programs for various vector sizes |
| |
| // Thread-specific kernels for each vector size: |
| // k[vector_size][thread_id] |
| KernelMatrix k; |
| |
| // Array of thread specific information |
| std::vector<ThreadInfo> tinfo; |
| |
| cl_uint threadCount; // Number of worker threads |
| cl_uint jobCount; // Number of jobs |
| cl_uint step; // step between each chunk and the next. |
| cl_uint scale; // stride between individual test values |
| float ulps; // max_allowed ulps |
| int ftz; // non-zero if running in flush to zero mode |
| |
| int isRangeLimited; // 1 if the function is only to be evaluated over a |
| // range |
| float half_sin_cos_tan_limit; |
| bool relaxedMode; // True if test is running in relaxed mode, false |
| // otherwise. |
| }; |
| |
| cl_int Test(cl_uint job_id, cl_uint thread_id, void *data) |
| { |
| TestInfo *job = (TestInfo *)data; |
| size_t buffer_elements = job->subBufferSize; |
| size_t buffer_size = buffer_elements * sizeof(cl_double); |
| cl_uint scale = job->scale; |
| cl_uint base = job_id * (cl_uint)job->step; |
| ThreadInfo *tinfo = &(job->tinfo[thread_id]); |
| float ulps = job->ulps; |
| dptr func = job->f->dfunc; |
| cl_int error; |
| int ftz = job->ftz; |
| bool relaxedMode = job->relaxedMode; |
| |
| Force64BitFPUPrecision(); |
| |
| // start the map of the output arrays |
| cl_event e[VECTOR_SIZE_COUNT]; |
| cl_ulong *out[VECTOR_SIZE_COUNT]; |
| for (auto j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++) |
| { |
| out[j] = (cl_ulong *)clEnqueueMapBuffer( |
| tinfo->tQueue, tinfo->outBuf[j], CL_FALSE, CL_MAP_WRITE, 0, |
| buffer_size, 0, NULL, e + j, &error); |
| if (error || NULL == out[j]) |
| { |
| vlog_error("Error: clEnqueueMapBuffer %d failed! err: %d\n", j, |
| error); |
| return error; |
| } |
| } |
| |
| // Get that moving |
| if ((error = clFlush(tinfo->tQueue))) vlog("clFlush failed\n"); |
| |
| // Write the new values to the input array |
| cl_double *p = (cl_double *)gIn + thread_id * buffer_elements; |
| for (size_t j = 0; j < buffer_elements; j++) |
| p[j] = DoubleFromUInt32(base + j * scale); |
| |
| if ((error = clEnqueueWriteBuffer(tinfo->tQueue, tinfo->inBuf, CL_FALSE, 0, |
| buffer_size, p, 0, NULL, NULL))) |
| { |
| vlog_error("Error: clEnqueueWriteBuffer failed! err: %d\n", error); |
| return error; |
| } |
| |
| for (auto j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++) |
| { |
| // Wait for the map to finish |
| if ((error = clWaitForEvents(1, e + j))) |
| { |
| vlog_error("Error: clWaitForEvents failed! err: %d\n", error); |
| return error; |
| } |
| if ((error = clReleaseEvent(e[j]))) |
| { |
| vlog_error("Error: clReleaseEvent failed! err: %d\n", error); |
| return error; |
| } |
| |
| // Fill the result buffer with garbage, so that old results don't carry |
| // over |
| uint32_t pattern = 0xffffdead; |
| memset_pattern4(out[j], &pattern, buffer_size); |
| if ((error = clEnqueueUnmapMemObject(tinfo->tQueue, tinfo->outBuf[j], |
| out[j], 0, NULL, NULL))) |
| { |
| vlog_error("Error: clEnqueueUnmapMemObject failed! err: %d\n", |
| error); |
| return error; |
| } |
| |
| // run the kernel |
| size_t vectorCount = |
| (buffer_elements + sizeValues[j] - 1) / sizeValues[j]; |
| cl_kernel kernel = job->k[j][thread_id]; // each worker thread has its |
| // own copy of the cl_kernel |
| cl_program program = job->programs[j]; |
| |
| if ((error = clSetKernelArg(kernel, 0, sizeof(tinfo->outBuf[j]), |
| &tinfo->outBuf[j]))) |
| { |
| LogBuildError(program); |
| return error; |
| } |
| if ((error = clSetKernelArg(kernel, 1, sizeof(tinfo->inBuf), |
| &tinfo->inBuf))) |
| { |
| LogBuildError(program); |
| return error; |
| } |
| |
| if ((error = clEnqueueNDRangeKernel(tinfo->tQueue, kernel, 1, NULL, |
| &vectorCount, NULL, 0, NULL, NULL))) |
| { |
| vlog_error("FAILED -- could not execute kernel\n"); |
| return error; |
| } |
| } |
| |
| |
| // Get that moving |
| if ((error = clFlush(tinfo->tQueue))) vlog("clFlush 2 failed\n"); |
| |
| if (gSkipCorrectnessTesting) return CL_SUCCESS; |
| |
| // Calculate the correctly rounded reference result |
| cl_double *r = (cl_double *)gOut_Ref + thread_id * buffer_elements; |
| cl_double *s = (cl_double *)p; |
| for (size_t j = 0; j < buffer_elements; j++) |
| r[j] = (cl_double)func.f_f(s[j]); |
| |
| // Read the data back -- no need to wait for the first N-1 buffers but wait |
| // for the last buffer. This is an in order queue. |
| for (auto j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++) |
| { |
| cl_bool blocking = (j + 1 < gMaxVectorSizeIndex) ? CL_FALSE : CL_TRUE; |
| out[j] = (cl_ulong *)clEnqueueMapBuffer( |
| tinfo->tQueue, tinfo->outBuf[j], blocking, CL_MAP_READ, 0, |
| buffer_size, 0, NULL, NULL, &error); |
| if (error || NULL == out[j]) |
| { |
| vlog_error("Error: clEnqueueMapBuffer %d failed! err: %d\n", j, |
| error); |
| return error; |
| } |
| } |
| |
| // Verify data |
| cl_ulong *t = (cl_ulong *)r; |
| for (size_t j = 0; j < buffer_elements; j++) |
| { |
| for (auto k = gMinVectorSizeIndex; k < gMaxVectorSizeIndex; k++) |
| { |
| cl_ulong *q = out[k]; |
| |
| // If we aren't getting the correctly rounded result |
| if (t[j] != q[j]) |
| { |
| cl_double test = ((cl_double *)q)[j]; |
| long double correct = func.f_f(s[j]); |
| float err = Bruteforce_Ulp_Error_Double(test, correct); |
| int fail = !(fabsf(err) <= ulps); |
| |
| if (fail) |
| { |
| if (ftz || relaxedMode) |
| { |
| // retry per section 6.5.3.2 |
| if (IsDoubleResultSubnormal(correct, ulps)) |
| { |
| fail = fail && (test != 0.0f); |
| if (!fail) err = 0.0f; |
| } |
| |
| // retry per section 6.5.3.3 |
| if (IsDoubleSubnormal(s[j])) |
| { |
| long double correct2 = func.f_f(0.0L); |
| long double correct3 = func.f_f(-0.0L); |
| float err2 = |
| Bruteforce_Ulp_Error_Double(test, correct2); |
| float err3 = |
| Bruteforce_Ulp_Error_Double(test, correct3); |
| fail = fail |
| && ((!(fabsf(err2) <= ulps)) |
| && (!(fabsf(err3) <= ulps))); |
| if (fabsf(err2) < fabsf(err)) err = err2; |
| if (fabsf(err3) < fabsf(err)) err = err3; |
| |
| // retry per section 6.5.3.4 |
| if (IsDoubleResultSubnormal(correct2, ulps) |
| || IsDoubleResultSubnormal(correct3, ulps)) |
| { |
| fail = fail && (test != 0.0f); |
| if (!fail) err = 0.0f; |
| } |
| } |
| } |
| } |
| if (fabsf(err) > tinfo->maxError) |
| { |
| tinfo->maxError = fabsf(err); |
| tinfo->maxErrorValue = s[j]; |
| } |
| if (fail) |
| { |
| vlog_error("\nERROR: %s%s: %f ulp error at %.13la " |
| "(0x%16.16llx): *%.13la vs. %.13la\n", |
| job->f->name, sizeNames[k], err, |
| ((cl_double *)gIn)[j], ((cl_ulong *)gIn)[j], |
| ((cl_double *)gOut_Ref)[j], test); |
| return -1; |
| } |
| } |
| } |
| } |
| |
| for (auto j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++) |
| { |
| if ((error = clEnqueueUnmapMemObject(tinfo->tQueue, tinfo->outBuf[j], |
| out[j], 0, NULL, NULL))) |
| { |
| vlog_error("Error: clEnqueueUnmapMemObject %d failed 2! err: %d\n", |
| j, error); |
| return error; |
| } |
| } |
| |
| if ((error = clFlush(tinfo->tQueue))) vlog("clFlush 3 failed\n"); |
| |
| |
| if (0 == (base & 0x0fffffff)) |
| { |
| if (gVerboseBruteForce) |
| { |
| vlog("base:%14u step:%10u scale:%10zd buf_elements:%10u ulps:%5.3f " |
| "ThreadCount:%2u\n", |
| base, job->step, buffer_elements, job->scale, job->ulps, |
| job->threadCount); |
| } |
| else |
| { |
| vlog("."); |
| } |
| fflush(stdout); |
| } |
| |
| return CL_SUCCESS; |
| } |
| |
| } // anonymous namespace |
| |
| int TestFunc_Double_Double(const Func *f, MTdata d, bool relaxedMode) |
| { |
| TestInfo test_info{}; |
| cl_int error; |
| float maxError = 0.0f; |
| double maxErrorVal = 0.0; |
| |
| logFunctionInfo(f->name, sizeof(cl_double), relaxedMode); |
| // Init test_info |
| test_info.threadCount = GetThreadCount(); |
| test_info.subBufferSize = BUFFER_SIZE |
| / (sizeof(cl_double) * RoundUpToNextPowerOfTwo(test_info.threadCount)); |
| test_info.scale = getTestScale(sizeof(cl_double)); |
| |
| test_info.step = (cl_uint)test_info.subBufferSize * test_info.scale; |
| if (test_info.step / test_info.subBufferSize != test_info.scale) |
| { |
| // there was overflow |
| test_info.jobCount = 1; |
| } |
| else |
| { |
| test_info.jobCount = (cl_uint)((1ULL << 32) / test_info.step); |
| } |
| |
| test_info.f = f; |
| test_info.ulps = f->double_ulps; |
| test_info.ftz = f->ftz || gForceFTZ; |
| test_info.relaxedMode = relaxedMode; |
| |
| // cl_kernels aren't thread safe, so we make one for each vector size for |
| // every thread |
| for (auto i = gMinVectorSizeIndex; i < gMaxVectorSizeIndex; i++) |
| { |
| test_info.k[i].resize(test_info.threadCount, nullptr); |
| } |
| |
| test_info.tinfo.resize(test_info.threadCount, ThreadInfo{}); |
| for (cl_uint i = 0; i < test_info.threadCount; i++) |
| { |
| cl_buffer_region region = { |
| i * test_info.subBufferSize * sizeof(cl_double), |
| test_info.subBufferSize * sizeof(cl_double) |
| }; |
| test_info.tinfo[i].inBuf = |
| clCreateSubBuffer(gInBuffer, CL_MEM_READ_ONLY, |
| CL_BUFFER_CREATE_TYPE_REGION, ®ion, &error); |
| if (error || NULL == test_info.tinfo[i].inBuf) |
| { |
| vlog_error("Error: Unable to create sub-buffer of gInBuffer for " |
| "region {%zd, %zd}\n", |
| region.origin, region.size); |
| goto exit; |
| } |
| |
| for (auto j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++) |
| { |
| test_info.tinfo[i].outBuf[j] = clCreateSubBuffer( |
| gOutBuffer[j], CL_MEM_WRITE_ONLY, CL_BUFFER_CREATE_TYPE_REGION, |
| ®ion, &error); |
| if (error || NULL == test_info.tinfo[i].outBuf[j]) |
| { |
| vlog_error("Error: Unable to create sub-buffer of " |
| "gOutBuffer[%d] for region {%zd, %zd}\n", |
| (int)j, region.origin, region.size); |
| goto exit; |
| } |
| } |
| test_info.tinfo[i].tQueue = |
| clCreateCommandQueue(gContext, gDevice, 0, &error); |
| if (NULL == test_info.tinfo[i].tQueue || error) |
| { |
| vlog_error("clCreateCommandQueue failed. (%d)\n", error); |
| goto exit; |
| } |
| } |
| |
| // Init the kernels |
| { |
| BuildKernelInfo build_info = { |
| gMinVectorSizeIndex, test_info.threadCount, test_info.k, |
| test_info.programs, f->nameInCode, relaxedMode |
| }; |
| if ((error = ThreadPool_Do(BuildKernelFn, |
| gMaxVectorSizeIndex - gMinVectorSizeIndex, |
| &build_info))) |
| goto exit; |
| } |
| |
| // Run the kernels |
| if (!gSkipCorrectnessTesting) |
| { |
| error = ThreadPool_Do(Test, test_info.jobCount, &test_info); |
| |
| // Accumulate the arithmetic errors |
| for (cl_uint i = 0; i < test_info.threadCount; i++) |
| { |
| if (test_info.tinfo[i].maxError > maxError) |
| { |
| maxError = test_info.tinfo[i].maxError; |
| maxErrorVal = test_info.tinfo[i].maxErrorValue; |
| } |
| } |
| |
| if (error) goto exit; |
| |
| if (gWimpyMode) |
| vlog("Wimp pass"); |
| else |
| vlog("passed"); |
| |
| vlog("\t%8.2f @ %a", maxError, maxErrorVal); |
| } |
| |
| vlog("\n"); |
| |
| exit: |
| // Release |
| for (auto i = gMinVectorSizeIndex; i < gMaxVectorSizeIndex; i++) |
| { |
| clReleaseProgram(test_info.programs[i]); |
| for (auto &kernel : test_info.k[i]) |
| { |
| clReleaseKernel(kernel); |
| } |
| } |
| |
| for (auto &threadInfo : test_info.tinfo) |
| { |
| clReleaseMemObject(threadInfo.inBuf); |
| for (auto j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++) |
| clReleaseMemObject(threadInfo.outBuf[j]); |
| clReleaseCommandQueue(threadInfo.tQueue); |
| } |
| |
| return error; |
| } |
