// // 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 "Utility.h" #include #include "FunctionList.h" int TestFunc_Float_Float_Float(const Func *f, MTdata, bool relaxedMode); int TestFunc_Double_Double_Double(const Func *f, MTdata, bool relaxedMode); int TestFunc_Float_Float_Float_nextafter(const Func *f, MTdata, bool relaxedMode); int TestFunc_Double_Double_Double_nextafter(const Func *f, MTdata, bool relaxedMode); extern const vtbl _binary = { "binary", TestFunc_Float_Float_Float, TestFunc_Double_Double_Double }; extern const vtbl _binary_nextafter = { "binary_nextafter", TestFunc_Float_Float_Float_nextafter, TestFunc_Double_Double_Double_nextafter }; const float twoToMinus126 = MAKE_HEX_FLOAT(0x1p-126f, 1, -126); const double twoToMinus1022 = MAKE_HEX_DOUBLE(0x1p-1022, 1, -1022); static int BuildKernel(const char *name, int vectorSize, cl_uint kernel_count, cl_kernel *k, cl_program *p, bool relaxedMode) { const char *c[] = { "__kernel void math_kernel", sizeNames[vectorSize], "( __global float", sizeNames[vectorSize], "* out, __global float", sizeNames[vectorSize], "* in1, __global float", sizeNames[vectorSize], "* in2 )\n" "{\n" " size_t i = get_global_id(0);\n" " out[i] = ", name, "( in1[i], in2[i] );\n" "}\n" }; const char *c3[] = { "__kernel void math_kernel", sizeNames[vectorSize], "( __global float* out, __global float* in, __global float* in2)\n" "{\n" " size_t i = get_global_id(0);\n" " if( i + 1 < get_global_size(0) )\n" " {\n" " float3 f0 = vload3( 0, in + 3 * i );\n" " float3 f1 = vload3( 0, in2 + 3 * i );\n" " f0 = ", name, "( f0, f1 );\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" " float3 f0;\n" " float3 f1;\n" " switch( parity )\n" " {\n" " case 1:\n" " f0 = (float3)( in[3*i], NAN, NAN ); \n" " f1 = (float3)( in2[3*i], NAN, NAN ); \n" " break;\n" " case 0:\n" " f0 = (float3)( in[3*i], in[3*i+1], NAN ); \n" " f1 = (float3)( in2[3*i], in2[3*i+1], NAN ); \n" " break;\n" " }\n" " f0 = ", name, "( f0, f1 );\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); } static int BuildKernelDouble(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], "* in1, __global double", sizeNames[vectorSize], "* in2 )\n" "{\n" " size_t i = get_global_id(0);\n" " out[i] = ", name, "( in1[i], in2[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, __global double* in2)\n" "{\n" " size_t i = get_global_id(0);\n" " if( i + 1 < get_global_size(0) )\n" " {\n" " double3 d0 = vload3( 0, in + 3 * i );\n" " double3 d1 = vload3( 0, in2 + 3 * i );\n" " d0 = ", name, "( d0, d1 );\n" " vstore3( d0, 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 d0;\n" " double3 d1;\n" " switch( parity )\n" " {\n" " case 1:\n" " d0 = (double3)( in[3*i], NAN, NAN ); \n" " d1 = (double3)( in2[3*i], NAN, NAN ); \n" " break;\n" " case 0:\n" " d0 = (double3)( in[3*i], in[3*i+1], NAN ); \n" " d1 = (double3)( in2[3*i], in2[3*i+1], NAN ); \n" " break;\n" " }\n" " d0 = ", name, "( d0, d1 );\n" " switch( parity )\n" " {\n" " case 0:\n" " out[3*i+1] = d0.y; \n" " // fall through\n" " case 1:\n" " out[3*i] = d0.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); } typedef struct BuildKernelInfo { cl_uint offset; // the first vector size to build cl_uint kernel_count; cl_kernel **kernels; cl_program *programs; const char *nameInCode; bool relaxedMode; // Whether to build with -cl-fast-relaxed-math. } BuildKernelInfo; static cl_int BuildKernel_FloatFn(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], info->programs + i, info->relaxedMode); } static cl_int BuildKernel_DoubleFn(cl_uint job_id, cl_uint thread_id UNUSED, void *p) { BuildKernelInfo *info = (BuildKernelInfo *)p; cl_uint i = info->offset + job_id; return BuildKernelDouble(info->nameInCode, i, info->kernel_count, info->kernels[i], info->programs + i, info->relaxedMode); } // A table of more difficult cases to get right static const float specialValuesFloat[] = { -NAN, -INFINITY, -FLT_MAX, MAKE_HEX_FLOAT(-0x1.000002p64f, -0x1000002L, 40), MAKE_HEX_FLOAT(-0x1.0p64f, -0x1L, 64), MAKE_HEX_FLOAT(-0x1.fffffep63f, -0x1fffffeL, 39), MAKE_HEX_FLOAT(-0x1.000002p63f, -0x1000002L, 39), MAKE_HEX_FLOAT(-0x1.0p63f, -0x1L, 63), MAKE_HEX_FLOAT(-0x1.fffffep62f, -0x1fffffeL, 38), MAKE_HEX_FLOAT(-0x1.000002p32f, -0x1000002L, 8), MAKE_HEX_FLOAT(-0x1.0p32f, -0x1L, 32), MAKE_HEX_FLOAT(-0x1.fffffep31f, -0x1fffffeL, 7), MAKE_HEX_FLOAT(-0x1.000002p31f, -0x1000002L, 7), MAKE_HEX_FLOAT(-0x1.0p31f, -0x1L, 31), MAKE_HEX_FLOAT(-0x1.fffffep30f, -0x1fffffeL, 6), -1000.f, -100.f, -4.0f, -3.5f, -3.0f, MAKE_HEX_FLOAT(-0x1.800002p1f, -0x1800002L, -23), -2.5f, MAKE_HEX_FLOAT(-0x1.7ffffep1f, -0x17ffffeL, -23), -2.0f, MAKE_HEX_FLOAT(-0x1.800002p0f, -0x1800002L, -24), -1.5f, MAKE_HEX_FLOAT(-0x1.7ffffep0f, -0x17ffffeL, -24), MAKE_HEX_FLOAT(-0x1.000002p0f, -0x1000002L, -24), -1.0f, MAKE_HEX_FLOAT(-0x1.fffffep-1f, -0x1fffffeL, -25), MAKE_HEX_FLOAT(-0x1.000002p-1f, -0x1000002L, -25), -0.5f, MAKE_HEX_FLOAT(-0x1.fffffep-2f, -0x1fffffeL, -26), MAKE_HEX_FLOAT(-0x1.000002p-2f, -0x1000002L, -26), -0.25f, MAKE_HEX_FLOAT(-0x1.fffffep-3f, -0x1fffffeL, -27), MAKE_HEX_FLOAT(-0x1.000002p-126f, -0x1000002L, -150), -FLT_MIN, MAKE_HEX_FLOAT(-0x0.fffffep-126f, -0x0fffffeL, -150), MAKE_HEX_FLOAT(-0x0.000ffep-126f, -0x0000ffeL, -150), MAKE_HEX_FLOAT(-0x0.0000fep-126f, -0x00000feL, -150), MAKE_HEX_FLOAT(-0x0.00000ep-126f, -0x000000eL, -150), MAKE_HEX_FLOAT(-0x0.00000cp-126f, -0x000000cL, -150), MAKE_HEX_FLOAT(-0x0.00000ap-126f, -0x000000aL, -150), MAKE_HEX_FLOAT(-0x0.000008p-126f, -0x0000008L, -150), MAKE_HEX_FLOAT(-0x0.000006p-126f, -0x0000006L, -150), MAKE_HEX_FLOAT(-0x0.000004p-126f, -0x0000004L, -150), MAKE_HEX_FLOAT(-0x0.000002p-126f, -0x0000002L, -150), -0.0f, +NAN, +INFINITY, +FLT_MAX, MAKE_HEX_FLOAT(+0x1.000002p64f, +0x1000002L, 40), MAKE_HEX_FLOAT(+0x1.0p64f, +0x1L, 64), MAKE_HEX_FLOAT(+0x1.fffffep63f, +0x1fffffeL, 39), MAKE_HEX_FLOAT(+0x1.000002p63f, +0x1000002L, 39), MAKE_HEX_FLOAT(+0x1.0p63f, +0x1L, 63), MAKE_HEX_FLOAT(+0x1.fffffep62f, +0x1fffffeL, 38), MAKE_HEX_FLOAT(+0x1.000002p32f, +0x1000002L, 8), MAKE_HEX_FLOAT(+0x1.0p32f, +0x1L, 32), MAKE_HEX_FLOAT(+0x1.fffffep31f, +0x1fffffeL, 7), MAKE_HEX_FLOAT(+0x1.000002p31f, +0x1000002L, 7), MAKE_HEX_FLOAT(+0x1.0p31f, +0x1L, 31), MAKE_HEX_FLOAT(+0x1.fffffep30f, +0x1fffffeL, 6), +1000.f, +100.f, +4.0f, +3.5f, +3.0f, MAKE_HEX_FLOAT(+0x1.800002p1f, +0x1800002L, -23), 2.5f, MAKE_HEX_FLOAT(+0x1.7ffffep1f, +0x17ffffeL, -23), +2.0f, MAKE_HEX_FLOAT(+0x1.800002p0f, +0x1800002L, -24), 1.5f, MAKE_HEX_FLOAT(+0x1.7ffffep0f, +0x17ffffeL, -24), MAKE_HEX_FLOAT(+0x1.000002p0f, +0x1000002L, -24), +1.0f, MAKE_HEX_FLOAT(+0x1.fffffep-1f, +0x1fffffeL, -25), MAKE_HEX_FLOAT(+0x1.000002p-1f, +0x1000002L, -25), +0.5f, MAKE_HEX_FLOAT(+0x1.fffffep-2f, +0x1fffffeL, -26), MAKE_HEX_FLOAT(+0x1.000002p-2f, +0x1000002L, -26), +0.25f, MAKE_HEX_FLOAT(+0x1.fffffep-3f, +0x1fffffeL, -27), MAKE_HEX_FLOAT(0x1.000002p-126f, 0x1000002L, -150), +FLT_MIN, MAKE_HEX_FLOAT(+0x0.fffffep-126f, +0x0fffffeL, -150), MAKE_HEX_FLOAT(+0x0.000ffep-126f, +0x0000ffeL, -150), MAKE_HEX_FLOAT(+0x0.0000fep-126f, +0x00000feL, -150), MAKE_HEX_FLOAT(+0x0.00000ep-126f, +0x000000eL, -150), MAKE_HEX_FLOAT(+0x0.00000cp-126f, +0x000000cL, -150), MAKE_HEX_FLOAT(+0x0.00000ap-126f, +0x000000aL, -150), MAKE_HEX_FLOAT(+0x0.000008p-126f, +0x0000008L, -150), MAKE_HEX_FLOAT(+0x0.000006p-126f, +0x0000006L, -150), MAKE_HEX_FLOAT(+0x0.000004p-126f, +0x0000004L, -150), MAKE_HEX_FLOAT(+0x0.000002p-126f, +0x0000002L, -150), +0.0f }; static const size_t specialValuesFloatCount = sizeof(specialValuesFloat) / sizeof(specialValuesFloat[0]); // Thread specific data for a worker thread typedef struct ThreadInfo { cl_mem inBuf; // input buffer for the thread cl_mem inBuf2; // 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 (param 1). Init to 0. double maxErrorValue2; // position of the max error value (param 2). Init // to 0. MTdata d; cl_command_queue tQueue; // per thread command queue to improve performance } ThreadInfo; typedef 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 cl_kernel *k[VECTOR_SIZE_COUNT]; // arrays of thread-specific kernels for each // worker thread: k[vector_size][thread_id] ThreadInfo * tinfo; // An array of thread specific information for each worker thread 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 isFDim; int skipNanInf; int isNextafter; bool relaxedMode; // True if test is running in relaxed mode, false // otherwise. } TestInfo; static cl_int TestFloat(cl_uint job_id, cl_uint thread_id, void *p); static int TestFunc_Float_Float_Float_common(const Func *f, MTdata d, int isNextafter, bool relaxedMode) { TestInfo test_info; cl_int error; size_t i, j; float maxError = 0.0f; double maxErrorVal = 0.0; double maxErrorVal2 = 0.0; int skipTestingRelaxed = 0; logFunctionInfo(f->name, sizeof(cl_float), relaxedMode); // Init test_info memset(&test_info, 0, sizeof(test_info)); test_info.threadCount = GetThreadCount(); test_info.subBufferSize = BUFFER_SIZE / (sizeof(cl_float) * RoundUpToNextPowerOfTwo(test_info.threadCount)); test_info.scale = getTestScale(sizeof(cl_float)); if (gWimpyMode) { test_info.subBufferSize = gWimpyBufferSize / (sizeof(cl_float) * RoundUpToNextPowerOfTwo(test_info.threadCount)); } 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 = gIsEmbedded ? f->float_embedded_ulps : f->float_ulps; test_info.ftz = f->ftz || gForceFTZ || 0 == (CL_FP_DENORM & gFloatCapabilities); test_info.relaxedMode = relaxedMode; test_info.isFDim = 0 == strcmp("fdim", f->nameInCode); test_info.skipNanInf = test_info.isFDim && !gInfNanSupport; test_info.isNextafter = isNextafter; // cl_kernels aren't thread safe, so we make one for each vector size for // every thread for (i = gMinVectorSizeIndex; i < gMaxVectorSizeIndex; i++) { size_t array_size = test_info.threadCount * sizeof(cl_kernel); test_info.k[i] = (cl_kernel *)malloc(array_size); if (NULL == test_info.k[i]) { vlog_error("Error: Unable to allocate storage for kernels!\n"); error = CL_OUT_OF_HOST_MEMORY; goto exit; } memset(test_info.k[i], 0, array_size); } test_info.tinfo = (ThreadInfo *)malloc(test_info.threadCount * sizeof(*test_info.tinfo)); if (NULL == test_info.tinfo) { vlog_error( "Error: Unable to allocate storage for thread specific data.\n"); error = CL_OUT_OF_HOST_MEMORY; goto exit; } memset(test_info.tinfo, 0, test_info.threadCount * sizeof(*test_info.tinfo)); for (i = 0; i < test_info.threadCount; i++) { cl_buffer_region region = { i * test_info.subBufferSize * sizeof(cl_float), test_info.subBufferSize * sizeof(cl_float) }; 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; } test_info.tinfo[i].inBuf2 = clCreateSubBuffer(gInBuffer2, CL_MEM_READ_ONLY, CL_BUFFER_CREATE_TYPE_REGION, ®ion, &error); if (error || NULL == test_info.tinfo[i].inBuf2) { vlog_error("Error: Unable to create sub-buffer of gInBuffer2 for " "region {%zd, %zd}\n", region.origin, region.size); goto exit; } for (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; } test_info.tinfo[i].d = init_genrand(genrand_int32(d)); } // Init the kernels { BuildKernelInfo build_info = { gMinVectorSizeIndex, test_info.threadCount, test_info.k, test_info.programs, f->nameInCode, relaxedMode }; if ((error = ThreadPool_Do(BuildKernel_FloatFn, gMaxVectorSizeIndex - gMinVectorSizeIndex, &build_info))) goto exit; } // Run the kernels if (!gSkipCorrectnessTesting) { error = ThreadPool_Do(TestFloat, test_info.jobCount, &test_info); // Accumulate the arithmetic errors for (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; maxErrorVal2 = test_info.tinfo[i].maxErrorValue2; } } if (error) goto exit; if (gWimpyMode) vlog("Wimp pass"); else vlog("passed"); } if (gMeasureTimes) { // Init input arrays cl_uint *p = (cl_uint *)gIn; cl_uint *p2 = (cl_uint *)gIn2; for (j = 0; j < BUFFER_SIZE / sizeof(float); j++) { p[j] = (genrand_int32(d) & ~0x40000000) | 0x20000000; p2[j] = 0x3fc00000; } if ((error = clEnqueueWriteBuffer(gQueue, gInBuffer, CL_FALSE, 0, BUFFER_SIZE, gIn, 0, NULL, NULL))) { vlog_error("\n*** Error %d in clEnqueueWriteBuffer ***\n", error); return error; } if ((error = clEnqueueWriteBuffer(gQueue, gInBuffer2, CL_FALSE, 0, BUFFER_SIZE, gIn2, 0, NULL, NULL))) { vlog_error("\n*** Error %d in clEnqueueWriteBuffer2 ***\n", error); return error; } // Run the kernels for (j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++) { size_t vectorSize = sizeof(cl_float) * sizeValues[j]; size_t localCount = (BUFFER_SIZE + vectorSize - 1) / vectorSize; // BUFFER_SIZE / vectorSize rounded up if ((error = clSetKernelArg(test_info.k[j][0], 0, sizeof(gOutBuffer[j]), &gOutBuffer[j]))) { LogBuildError(test_info.programs[j]); goto exit; } if ((error = clSetKernelArg(test_info.k[j][0], 1, sizeof(gInBuffer), &gInBuffer))) { LogBuildError(test_info.programs[j]); goto exit; } if ((error = clSetKernelArg(test_info.k[j][0], 2, sizeof(gInBuffer2), &gInBuffer2))) { LogBuildError(test_info.programs[j]); goto exit; } double sum = 0.0; double bestTime = INFINITY; for (i = 0; i < PERF_LOOP_COUNT; i++) { uint64_t startTime = GetTime(); if ((error = clEnqueueNDRangeKernel(gQueue, test_info.k[j][0], 1, NULL, &localCount, NULL, 0, NULL, NULL))) { vlog_error("FAILED -- could not execute kernel\n"); goto exit; } // Make sure OpenCL is done if ((error = clFinish(gQueue))) { vlog_error("Error %d at clFinish\n", error); goto exit; } uint64_t endTime = GetTime(); double time = SubtractTime(endTime, startTime); sum += time; if (time < bestTime) bestTime = time; } if (gReportAverageTimes) bestTime = sum / PERF_LOOP_COUNT; double clocksPerOp = bestTime * (double)gDeviceFrequency * gComputeDevices * gSimdSize * 1e6 / (BUFFER_SIZE / sizeof(float)); vlog_perf(clocksPerOp, LOWER_IS_BETTER, "clocks / element", "%sf%s", f->name, sizeNames[j]); } } if (!gSkipCorrectnessTesting) vlog("\t%8.2f @ {%a, %a}", maxError, maxErrorVal, maxErrorVal2); vlog("\n"); exit: for (i = gMinVectorSizeIndex; i < gMaxVectorSizeIndex; i++) { clReleaseProgram(test_info.programs[i]); if (test_info.k[i]) { for (j = 0; j < test_info.threadCount; j++) clReleaseKernel(test_info.k[i][j]); free(test_info.k[i]); } } if (test_info.tinfo) { for (i = 0; i < test_info.threadCount; i++) { free_mtdata(test_info.tinfo[i].d); clReleaseMemObject(test_info.tinfo[i].inBuf); clReleaseMemObject(test_info.tinfo[i].inBuf2); for (j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++) clReleaseMemObject(test_info.tinfo[i].outBuf[j]); clReleaseCommandQueue(test_info.tinfo[i].tQueue); } free(test_info.tinfo); } return error; } static cl_int TestFloat(cl_uint job_id, cl_uint thread_id, void *data) { const TestInfo *job = (const TestInfo *)data; size_t buffer_elements = job->subBufferSize; size_t buffer_size = buffer_elements * sizeof(cl_float); cl_uint base = job_id * (cl_uint)job->step; ThreadInfo *tinfo = job->tinfo + thread_id; fptr func = job->f->func; int ftz = job->ftz; bool relaxedMode = job->relaxedMode; float ulps = getAllowedUlpError(job->f, relaxedMode); MTdata d = tinfo->d; cl_uint j, k; cl_int error; cl_uchar *overflow = (cl_uchar *)malloc(buffer_size); const char *name = job->f->name; int isFDim = job->isFDim; int skipNanInf = job->skipNanInf; int isNextafter = job->isNextafter; cl_uint *t = 0; cl_float *r = 0; cl_float *s = 0; cl_float *s2 = 0; cl_int copysign_test = 0; RoundingMode oldRoundMode; int skipVerification = 0; if (relaxedMode) { func = job->f->rfunc; if (strcmp(name, "pow") == 0 && gFastRelaxedDerived) { ulps = INFINITY; skipVerification = 1; } } // start the map of the output arrays cl_event e[VECTOR_SIZE_COUNT]; cl_uint *out[VECTOR_SIZE_COUNT]; for (j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++) { out[j] = (cl_uint *)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"); // Init input array cl_uint *p = (cl_uint *)gIn + thread_id * buffer_elements; cl_uint *p2 = (cl_uint *)gIn2 + thread_id * buffer_elements; j = 0; int totalSpecialValueCount = specialValuesFloatCount * specialValuesFloatCount; int indx = (totalSpecialValueCount - 1) / buffer_elements; if (job_id <= (cl_uint)indx) { // test edge cases float *fp = (float *)p; float *fp2 = (float *)p2; uint32_t x, y; x = (job_id * buffer_elements) % specialValuesFloatCount; y = (job_id * buffer_elements) / specialValuesFloatCount; for (; j < buffer_elements; j++) { fp[j] = specialValuesFloat[x]; fp2[j] = specialValuesFloat[y]; ++x; if (x >= specialValuesFloatCount) { x = 0; y++; if (y >= specialValuesFloatCount) break; } } } // Init any remaining values. for (; j < buffer_elements; j++) { p[j] = genrand_int32(d); p2[j] = genrand_int32(d); } 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); goto exit; } if ((error = clEnqueueWriteBuffer(tinfo->tQueue, tinfo->inBuf2, CL_FALSE, 0, buffer_size, p2, 0, NULL, NULL))) { vlog_error("Error: clEnqueueWriteBuffer failed! err: %d\n", error); goto exit; } for (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); goto exit; } if ((error = clReleaseEvent(e[j]))) { vlog_error("Error: clReleaseEvent failed! err: %d\n", error); goto exit; } // 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: clEnqueueMapBuffer failed! err: %d\n", error); goto exit; } // 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 = clSetKernelArg(kernel, 2, sizeof(tinfo->inBuf2), &tinfo->inBuf2))) { 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"); goto exit; } } // Get that moving if ((error = clFlush(tinfo->tQueue))) vlog("clFlush 2 failed\n"); if (gSkipCorrectnessTesting) { if ((error = clFinish(tinfo->tQueue))) { vlog_error("Error: clFinish failed! err: %d\n", error); goto exit; } free(overflow); return CL_SUCCESS; } FPU_mode_type oldMode; oldRoundMode = kRoundToNearestEven; if (isFDim) { // Calculate the correctly rounded reference result memset(&oldMode, 0, sizeof(oldMode)); if (ftz) ForceFTZ(&oldMode); // Set the rounding mode to match the device if (gIsInRTZMode) oldRoundMode = set_round(kRoundTowardZero, kfloat); } if (!strcmp(name, "copysign")) copysign_test = 1; #define ref_func(s, s2) (copysign_test ? func.f_ff_f(s, s2) : func.f_ff(s, s2)) // Calculate the correctly rounded reference result r = (float *)gOut_Ref + thread_id * buffer_elements; s = (float *)gIn + thread_id * buffer_elements; s2 = (float *)gIn2 + thread_id * buffer_elements; if (skipNanInf) { for (j = 0; j < buffer_elements; j++) { feclearexcept(FE_OVERFLOW); r[j] = (float)ref_func(s[j], s2[j]); overflow[j] = FE_OVERFLOW == (FE_OVERFLOW & fetestexcept(FE_OVERFLOW)); } } else { for (j = 0; j < buffer_elements; j++) r[j] = (float)ref_func(s[j], s2[j]); } if (isFDim && ftz) RestoreFPState(&oldMode); // Read the data back -- no need to wait for the first N-1 buffers. This is // an in order queue. for (j = gMinVectorSizeIndex; j + 1 < gMaxVectorSizeIndex; j++) { out[j] = (cl_uint *)clEnqueueMapBuffer( tinfo->tQueue, tinfo->outBuf[j], CL_FALSE, 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); goto exit; } } // Wait for the last buffer out[j] = (cl_uint *)clEnqueueMapBuffer(tinfo->tQueue, tinfo->outBuf[j], CL_TRUE, 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); goto exit; } if (!skipVerification) { // Verify data t = (cl_uint *)r; for (j = 0; j < buffer_elements; j++) { for (k = gMinVectorSizeIndex; k < gMaxVectorSizeIndex; k++) { cl_uint *q = out[k]; // If we aren't getting the correctly rounded result if (t[j] != q[j]) { float test = ((float *)q)[j]; double correct = ref_func(s[j], s2[j]); // Per section 10 paragraph 6, accept any result if an input // or output is a infinity or NaN or overflow As per // OpenCL 2.0 spec, section 5.8.4.3, enabling // fast-relaxed-math mode also enables -cl-finite-math-only // optimization. This optimization allows to assume that // arguments and results are not NaNs or +/-INFs. Hence, // accept any result if inputs or results are NaNs or INFs. if (relaxedMode || skipNanInf) { if (skipNanInf && overflow[j]) continue; // Note: no double rounding here. Reference functions // calculate in single precision. if (IsFloatInfinity(correct) || IsFloatNaN(correct) || IsFloatInfinity(s2[j]) || IsFloatNaN(s2[j]) || IsFloatInfinity(s[j]) || IsFloatNaN(s[j])) continue; } float err = Ulp_Error(test, correct); int fail = !(fabsf(err) <= ulps); if (fail && ftz) { // retry per section 6.5.3.2 if (IsFloatResultSubnormal(correct, ulps)) { fail = fail && (test != 0.0f); if (!fail) err = 0.0f; } // nextafter on FTZ platforms may return the smallest // normal float (2^-126) given a denormal or a zero // as the first argument. The rationale here is that // nextafter flushes the argument to zero and then // returns the next representable number in the // direction of the second argument, and since // denorms are considered as zero, the smallest // normal number is the next representable number. // In which case, it should have the same sign as the // second argument. if (isNextafter) { if (IsFloatSubnormal(s[j]) || s[j] == 0.0f) { float value = copysignf(twoToMinus126, s2[j]); fail = fail && (test != value); if (!fail) err = 0.0f; } } else { // retry per section 6.5.3.3 if (IsFloatSubnormal(s[j])) { double correct2, correct3; float err2, err3; if (skipNanInf) feclearexcept(FE_OVERFLOW); correct2 = ref_func(0.0, s2[j]); correct3 = ref_func(-0.0, s2[j]); // Per section 10 paragraph 6, accept any result // if an input or output is a infinity or NaN or // overflow As per OpenCL 2.0 spec, // section 5.8.4.3, enabling fast-relaxed-math // mode also enables -cl-finite-math-only // optimization. This optimization allows to // assume that arguments and results are not // NaNs or +/-INFs. Hence, accept any result if // inputs or results are NaNs or INFs. if (relaxedMode || skipNanInf) { if (fetestexcept(FE_OVERFLOW) && skipNanInf) continue; // Note: no double rounding here. Reference // functions calculate in single precision. if (IsFloatInfinity(correct2) || IsFloatNaN(correct2) || IsFloatInfinity(correct3) || IsFloatNaN(correct3)) continue; } err2 = Ulp_Error(test, correct2); err3 = Ulp_Error(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 (IsFloatResultSubnormal(correct2, ulps) || IsFloatResultSubnormal(correct3, ulps)) { fail = fail && (test != 0.0f); if (!fail) err = 0.0f; } // try with both args as zero if (IsFloatSubnormal(s2[j])) { double correct4, correct5; float err4, err5; if (skipNanInf) feclearexcept(FE_OVERFLOW); correct2 = ref_func(0.0, 0.0); correct3 = ref_func(-0.0, 0.0); correct4 = ref_func(0.0, -0.0); correct5 = ref_func(-0.0, -0.0); // Per section 10 paragraph 6, accept any // result if an input or output is a // infinity or NaN or overflow As per // OpenCL 2.0 spec, section 5.8.4.3, // enabling fast-relaxed-math mode also // enables -cl-finite-math-only // optimization. This optimization allows to // assume that arguments and results are not // NaNs or +/-INFs. Hence, accept any result // if inputs or results are NaNs or INFs. if (relaxedMode || skipNanInf) { if (fetestexcept(FE_OVERFLOW) && skipNanInf) continue; // Note: no double rounding here. // Reference functions calculate in // single precision. if (IsFloatInfinity(correct2) || IsFloatNaN(correct2) || IsFloatInfinity(correct3) || IsFloatNaN(correct3) || IsFloatInfinity(correct4) || IsFloatNaN(correct4) || IsFloatInfinity(correct5) || IsFloatNaN(correct5)) continue; } err2 = Ulp_Error(test, correct2); err3 = Ulp_Error(test, correct3); err4 = Ulp_Error(test, correct4); err5 = Ulp_Error(test, correct5); fail = fail && ((!(fabsf(err2) <= ulps)) && (!(fabsf(err3) <= ulps)) && (!(fabsf(err4) <= ulps)) && (!(fabsf(err5) <= ulps))); if (fabsf(err2) < fabsf(err)) err = err2; if (fabsf(err3) < fabsf(err)) err = err3; if (fabsf(err4) < fabsf(err)) err = err4; if (fabsf(err5) < fabsf(err)) err = err5; // retry per section 6.5.3.4 if (IsFloatResultSubnormal(correct2, ulps) || IsFloatResultSubnormal(correct3, ulps) || IsFloatResultSubnormal(correct4, ulps) || IsFloatResultSubnormal(correct5, ulps)) { fail = fail && (test != 0.0f); if (!fail) err = 0.0f; } } } else if (IsFloatSubnormal(s2[j])) { double correct2, correct3; float err2, err3; if (skipNanInf) feclearexcept(FE_OVERFLOW); correct2 = ref_func(s[j], 0.0); correct3 = ref_func(s[j], -0.0); // Per section 10 paragraph 6, accept any result // if an input or output is a infinity or NaN or // overflow As per OpenCL 2.0 spec, // section 5.8.4.3, enabling fast-relaxed-math // mode also enables -cl-finite-math-only // optimization. This optimization allows to // assume that arguments and results are not // NaNs or +/-INFs. Hence, accept any result if // inputs or results are NaNs or INFs. if (relaxedMode || skipNanInf) { // Note: no double rounding here. Reference // functions calculate in single precision. if (overflow[j] && skipNanInf) continue; if (IsFloatInfinity(correct2) || IsFloatNaN(correct2) || IsFloatInfinity(correct3) || IsFloatNaN(correct3)) continue; } err2 = Ulp_Error(test, correct2); err3 = Ulp_Error(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 (IsFloatResultSubnormal(correct2, ulps) || IsFloatResultSubnormal(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]; tinfo->maxErrorValue2 = s2[j]; } if (fail) { vlog_error( "\nERROR: %s%s: %f ulp error at {%a (0x%x), %a " "(0x%x)}: *%a vs. %a (0x%8.8x) at index: %d\n", name, sizeNames[k], err, s[j], ((cl_uint *)s)[j], s2[j], ((cl_uint *)s2)[j], r[j], test, ((cl_uint *)&test)[0], j); error = -1; goto exit; } } } } } if (isFDim && gIsInRTZMode) (void)set_round(oldRoundMode, kfloat); for (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:%10zu buf_elements:%10u ulps:%5.3f " "ThreadCount:%2u\n", base, job->step, job->scale, buffer_elements, job->ulps, job->threadCount); } else { vlog("."); } fflush(stdout); } exit: if (overflow) free(overflow); return error; } // A table of more difficult cases to get right static const double specialValuesDouble[] = { -NAN, -INFINITY, -DBL_MAX, MAKE_HEX_DOUBLE(-0x1.0000000000001p64, -0x10000000000001LL, 12), MAKE_HEX_DOUBLE(-0x1.0p64, -0x1LL, 64), MAKE_HEX_DOUBLE(-0x1.fffffffffffffp63, -0x1fffffffffffffLL, 11), MAKE_HEX_DOUBLE(-0x1.0000000000001p63, -0x10000000000001LL, 11), MAKE_HEX_DOUBLE(-0x1.0p63, -0x1LL, 63), MAKE_HEX_DOUBLE(-0x1.fffffffffffffp62, -0x1fffffffffffffLL, 10), MAKE_HEX_DOUBLE(-0x1.000002p32, -0x1000002LL, 8), MAKE_HEX_DOUBLE(-0x1.0p32, -0x1LL, 32), MAKE_HEX_DOUBLE(-0x1.fffffffffffffp31, -0x1fffffffffffffLL, -21), MAKE_HEX_DOUBLE(-0x1.0000000000001p31, -0x10000000000001LL, -21), MAKE_HEX_DOUBLE(-0x1.0p31, -0x1LL, 31), MAKE_HEX_DOUBLE(-0x1.fffffffffffffp30, -0x1fffffffffffffLL, -22), -1000., -100., -4.0, -3.5, -3.0, MAKE_HEX_DOUBLE(-0x1.8000000000001p1, -0x18000000000001LL, -51), -2.5, MAKE_HEX_DOUBLE(-0x1.7ffffffffffffp1, -0x17ffffffffffffLL, -51), -2.0, MAKE_HEX_DOUBLE(-0x1.8000000000001p0, -0x18000000000001LL, -52), -1.5, MAKE_HEX_DOUBLE(-0x1.7ffffffffffffp0, -0x17ffffffffffffLL, -52), MAKE_HEX_DOUBLE(-0x1.0000000000001p0, -0x10000000000001LL, -52), -1.0, MAKE_HEX_DOUBLE(-0x1.fffffffffffffp-1, -0x1fffffffffffffLL, -53), MAKE_HEX_DOUBLE(-0x1.0000000000001p-1, -0x10000000000001LL, -53), -0.5, MAKE_HEX_DOUBLE(-0x1.fffffffffffffp-2, -0x1fffffffffffffLL, -54), MAKE_HEX_DOUBLE(-0x1.0000000000001p-2, -0x10000000000001LL, -54), -0.25, MAKE_HEX_DOUBLE(-0x1.fffffffffffffp-3, -0x1fffffffffffffLL, -55), MAKE_HEX_DOUBLE(-0x1.0000000000001p-1022, -0x10000000000001LL, -1074), -DBL_MIN, MAKE_HEX_DOUBLE(-0x0.fffffffffffffp-1022, -0x0fffffffffffffLL, -1074), MAKE_HEX_DOUBLE(-0x0.0000000000fffp-1022, -0x00000000000fffLL, -1074), MAKE_HEX_DOUBLE(-0x0.00000000000fep-1022, -0x000000000000feLL, -1074), MAKE_HEX_DOUBLE(-0x0.000000000000ep-1022, -0x0000000000000eLL, -1074), MAKE_HEX_DOUBLE(-0x0.000000000000cp-1022, -0x0000000000000cLL, -1074), MAKE_HEX_DOUBLE(-0x0.000000000000ap-1022, -0x0000000000000aLL, -1074), MAKE_HEX_DOUBLE(-0x0.0000000000008p-1022, -0x00000000000008LL, -1074), MAKE_HEX_DOUBLE(-0x0.0000000000007p-1022, -0x00000000000007LL, -1074), MAKE_HEX_DOUBLE(-0x0.0000000000006p-1022, -0x00000000000006LL, -1074), MAKE_HEX_DOUBLE(-0x0.0000000000005p-1022, -0x00000000000005LL, -1074), MAKE_HEX_DOUBLE(-0x0.0000000000004p-1022, -0x00000000000004LL, -1074), MAKE_HEX_DOUBLE(-0x0.0000000000003p-1022, -0x00000000000003LL, -1074), MAKE_HEX_DOUBLE(-0x0.0000000000002p-1022, -0x00000000000002LL, -1074), MAKE_HEX_DOUBLE(-0x0.0000000000001p-1022, -0x00000000000001LL, -1074), -0.0, +NAN, +INFINITY, +DBL_MAX, MAKE_HEX_DOUBLE(+0x1.0000000000001p64, +0x10000000000001LL, 12), MAKE_HEX_DOUBLE(+0x1.0p64, +0x1LL, 64), MAKE_HEX_DOUBLE(+0x1.fffffffffffffp63, +0x1fffffffffffffLL, 11), MAKE_HEX_DOUBLE(+0x1.0000000000001p63, +0x10000000000001LL, 11), MAKE_HEX_DOUBLE(+0x1.0p63, +0x1LL, 63), MAKE_HEX_DOUBLE(+0x1.fffffffffffffp62, +0x1fffffffffffffLL, 10), MAKE_HEX_DOUBLE(+0x1.000002p32, +0x1000002LL, 8), MAKE_HEX_DOUBLE(+0x1.0p32, +0x1LL, 32), MAKE_HEX_DOUBLE(+0x1.fffffffffffffp31, +0x1fffffffffffffLL, -21), MAKE_HEX_DOUBLE(+0x1.0000000000001p31, +0x10000000000001LL, -21), MAKE_HEX_DOUBLE(+0x1.0p31, +0x1LL, 31), MAKE_HEX_DOUBLE(+0x1.fffffffffffffp30, +0x1fffffffffffffLL, -22), +1000., +100., +4.0, +3.5, +3.0, MAKE_HEX_DOUBLE(+0x1.8000000000001p1, +0x18000000000001LL, -51), +2.5, MAKE_HEX_DOUBLE(+0x1.7ffffffffffffp1, +0x17ffffffffffffLL, -51), +2.0, MAKE_HEX_DOUBLE(+0x1.8000000000001p0, +0x18000000000001LL, -52), +1.5, MAKE_HEX_DOUBLE(+0x1.7ffffffffffffp0, +0x17ffffffffffffLL, -52), MAKE_HEX_DOUBLE(-0x1.0000000000001p0, -0x10000000000001LL, -52), +1.0, MAKE_HEX_DOUBLE(+0x1.fffffffffffffp-1, +0x1fffffffffffffLL, -53), MAKE_HEX_DOUBLE(+0x1.0000000000001p-1, +0x10000000000001LL, -53), +0.5, MAKE_HEX_DOUBLE(+0x1.fffffffffffffp-2, +0x1fffffffffffffLL, -54), MAKE_HEX_DOUBLE(+0x1.0000000000001p-2, +0x10000000000001LL, -54), +0.25, MAKE_HEX_DOUBLE(+0x1.fffffffffffffp-3, +0x1fffffffffffffLL, -55), MAKE_HEX_DOUBLE(+0x1.0000000000001p-1022, +0x10000000000001LL, -1074), +DBL_MIN, MAKE_HEX_DOUBLE(+0x0.fffffffffffffp-1022, +0x0fffffffffffffLL, -1074), MAKE_HEX_DOUBLE(+0x0.0000000000fffp-1022, +0x00000000000fffLL, -1074), MAKE_HEX_DOUBLE(+0x0.00000000000fep-1022, +0x000000000000feLL, -1074), MAKE_HEX_DOUBLE(+0x0.000000000000ep-1022, +0x0000000000000eLL, -1074), MAKE_HEX_DOUBLE(+0x0.000000000000cp-1022, +0x0000000000000cLL, -1074), MAKE_HEX_DOUBLE(+0x0.000000000000ap-1022, +0x0000000000000aLL, -1074), MAKE_HEX_DOUBLE(+0x0.0000000000008p-1022, +0x00000000000008LL, -1074), MAKE_HEX_DOUBLE(+0x0.0000000000007p-1022, +0x00000000000007LL, -1074), MAKE_HEX_DOUBLE(+0x0.0000000000006p-1022, +0x00000000000006LL, -1074), MAKE_HEX_DOUBLE(+0x0.0000000000005p-1022, +0x00000000000005LL, -1074), MAKE_HEX_DOUBLE(+0x0.0000000000004p-1022, +0x00000000000004LL, -1074), MAKE_HEX_DOUBLE(+0x0.0000000000003p-1022, +0x00000000000003LL, -1074), MAKE_HEX_DOUBLE(+0x0.0000000000002p-1022, +0x00000000000002LL, -1074), MAKE_HEX_DOUBLE(+0x0.0000000000001p-1022, +0x00000000000001LL, -1074), +0.0, }; static size_t specialValuesDoubleCount = sizeof(specialValuesDouble) / sizeof(specialValuesDouble[0]); static cl_int TestDouble(cl_uint job_id, cl_uint thread_id, void *p); static int TestFunc_Double_Double_Double_common(const Func *f, MTdata d, int isNextafter, bool relaxedMode) { TestInfo test_info; cl_int error; size_t i, j; float maxError = 0.0f; double maxErrorVal = 0.0; double maxErrorVal2 = 0.0; logFunctionInfo(f->name, sizeof(cl_double), relaxedMode); // Init test_info memset(&test_info, 0, sizeof(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)); if (gWimpyMode) { test_info.subBufferSize = gWimpyBufferSize / (sizeof(cl_double) * RoundUpToNextPowerOfTwo(test_info.threadCount)); } 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.isFDim = 0 == strcmp("fdim", f->nameInCode); test_info.skipNanInf = 0; test_info.isNextafter = isNextafter; // cl_kernels aren't thread safe, so we make one for each vector size for // every thread for (i = gMinVectorSizeIndex; i < gMaxVectorSizeIndex; i++) { size_t array_size = test_info.threadCount * sizeof(cl_kernel); test_info.k[i] = (cl_kernel *)malloc(array_size); if (NULL == test_info.k[i]) { vlog_error("Error: Unable to allocate storage for kernels!\n"); error = CL_OUT_OF_HOST_MEMORY; goto exit; } memset(test_info.k[i], 0, array_size); } test_info.tinfo = (ThreadInfo *)malloc(test_info.threadCount * sizeof(*test_info.tinfo)); if (NULL == test_info.tinfo) { vlog_error( "Error: Unable to allocate storage for thread specific data.\n"); error = CL_OUT_OF_HOST_MEMORY; goto exit; } memset(test_info.tinfo, 0, test_info.threadCount * sizeof(*test_info.tinfo)); for (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; } test_info.tinfo[i].inBuf2 = clCreateSubBuffer(gInBuffer2, 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 (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 gInBuffer " "for region {%zd, %zd}\n", 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; } test_info.tinfo[i].d = init_genrand(genrand_int32(d)); } // Init the kernels { BuildKernelInfo build_info = { gMinVectorSizeIndex, test_info.threadCount, test_info.k, test_info.programs, f->nameInCode, relaxedMode }; if ((error = ThreadPool_Do(BuildKernel_DoubleFn, gMaxVectorSizeIndex - gMinVectorSizeIndex, &build_info))) goto exit; } // Run the kernels if (!gSkipCorrectnessTesting) { error = ThreadPool_Do(TestDouble, test_info.jobCount, &test_info); // Accumulate the arithmetic errors for (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; maxErrorVal2 = test_info.tinfo[i].maxErrorValue2; } } if (error) goto exit; if (gWimpyMode) vlog("Wimp pass"); else vlog("passed"); } if (gMeasureTimes) { // Init input arrays double *p = (double *)gIn; double *p2 = (double *)gIn2; for (j = 0; j < BUFFER_SIZE / sizeof(cl_double); j++) { p[j] = DoubleFromUInt32(genrand_int32(d)); p2[j] = DoubleFromUInt32(genrand_int32(d)); } if ((error = clEnqueueWriteBuffer(gQueue, gInBuffer, CL_FALSE, 0, BUFFER_SIZE, gIn, 0, NULL, NULL))) { vlog_error("\n*** Error %d in clEnqueueWriteBuffer ***\n", error); return error; } if ((error = clEnqueueWriteBuffer(gQueue, gInBuffer2, CL_FALSE, 0, BUFFER_SIZE, gIn2, 0, NULL, NULL))) { vlog_error("\n*** Error %d in clEnqueueWriteBuffer2 ***\n", error); return error; } // Run the kernels for (j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++) { size_t vectorSize = sizeof(cl_double) * sizeValues[j]; size_t localCount = (BUFFER_SIZE + vectorSize - 1) / vectorSize; // BUFFER_SIZE / vectorSize rounded up if ((error = clSetKernelArg(test_info.k[j][0], 0, sizeof(gOutBuffer[j]), &gOutBuffer[j]))) { LogBuildError(test_info.programs[j]); goto exit; } if ((error = clSetKernelArg(test_info.k[j][0], 1, sizeof(gInBuffer), &gInBuffer))) { LogBuildError(test_info.programs[j]); goto exit; } if ((error = clSetKernelArg(test_info.k[j][0], 2, sizeof(gInBuffer2), &gInBuffer2))) { LogBuildError(test_info.programs[j]); goto exit; } double sum = 0.0; double bestTime = INFINITY; for (i = 0; i < PERF_LOOP_COUNT; i++) { uint64_t startTime = GetTime(); if ((error = clEnqueueNDRangeKernel(gQueue, test_info.k[j][0], 1, NULL, &localCount, NULL, 0, NULL, NULL))) { vlog_error("FAILED -- could not execute kernel\n"); goto exit; } // Make sure OpenCL is done if ((error = clFinish(gQueue))) { vlog_error("Error %d at clFinish\n", error); goto exit; } uint64_t endTime = GetTime(); double time = SubtractTime(endTime, startTime); sum += time; if (time < bestTime) bestTime = time; } if (gReportAverageTimes) bestTime = sum / PERF_LOOP_COUNT; double clocksPerOp = bestTime * (double)gDeviceFrequency * gComputeDevices * gSimdSize * 1e6 / (BUFFER_SIZE / sizeof(double)); vlog_perf(clocksPerOp, LOWER_IS_BETTER, "clocks / element", "%sD%s", f->name, sizeNames[j]); } for (; j < gMaxVectorSizeIndex; j++) vlog("\t -- "); } if (!gSkipCorrectnessTesting) vlog("\t%8.2f @ {%a, %a}", maxError, maxErrorVal, maxErrorVal2); vlog("\n"); exit: // Release for (i = gMinVectorSizeIndex; i < gMaxVectorSizeIndex; i++) { clReleaseProgram(test_info.programs[i]); if (test_info.k[i]) { for (j = 0; j < test_info.threadCount; j++) clReleaseKernel(test_info.k[i][j]); free(test_info.k[i]); } } if (test_info.tinfo) { for (i = 0; i < test_info.threadCount; i++) { free_mtdata(test_info.tinfo[i].d); clReleaseMemObject(test_info.tinfo[i].inBuf); clReleaseMemObject(test_info.tinfo[i].inBuf2); for (j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++) clReleaseMemObject(test_info.tinfo[i].outBuf[j]); clReleaseCommandQueue(test_info.tinfo[i].tQueue); } free(test_info.tinfo); } return error; } static cl_int TestDouble(cl_uint job_id, cl_uint thread_id, void *data) { const TestInfo *job = (const TestInfo *)data; size_t buffer_elements = job->subBufferSize; size_t buffer_size = buffer_elements * sizeof(cl_double); cl_uint base = job_id * (cl_uint)job->step; ThreadInfo *tinfo = job->tinfo + thread_id; float ulps = job->ulps; dptr func = job->f->dfunc; int ftz = job->ftz; MTdata d = tinfo->d; cl_uint j, k; cl_int error; const char *name = job->f->name; int isNextafter = job->isNextafter; cl_ulong *t; cl_double *r; cl_double *s; cl_double *s2; Force64BitFPUPrecision(); // start the map of the output arrays cl_event e[VECTOR_SIZE_COUNT]; cl_ulong *out[VECTOR_SIZE_COUNT]; for (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"); // Init input array cl_ulong *p = (cl_ulong *)gIn + thread_id * buffer_elements; cl_ulong *p2 = (cl_ulong *)gIn2 + thread_id * buffer_elements; j = 0; int totalSpecialValueCount = specialValuesDoubleCount * specialValuesDoubleCount; int indx = (totalSpecialValueCount - 1) / buffer_elements; if (job_id <= (cl_uint)indx) { // test edge cases cl_double *fp = (cl_double *)p; cl_double *fp2 = (cl_double *)p2; uint32_t x, y; x = (job_id * buffer_elements) % specialValuesDoubleCount; y = (job_id * buffer_elements) / specialValuesDoubleCount; for (; j < buffer_elements; j++) { fp[j] = specialValuesDouble[x]; fp2[j] = specialValuesDouble[y]; if (++x >= specialValuesDoubleCount) { x = 0; y++; if (y >= specialValuesDoubleCount) break; } } } // Init any remaining values. for (; j < buffer_elements; j++) { p[j] = genrand_int64(d); p2[j] = genrand_int64(d); } 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); goto exit; } if ((error = clEnqueueWriteBuffer(tinfo->tQueue, tinfo->inBuf2, CL_FALSE, 0, buffer_size, p2, 0, NULL, NULL))) { vlog_error("Error: clEnqueueWriteBuffer failed! err: %d\n", error); goto exit; } for (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); goto exit; } if ((error = clReleaseEvent(e[j]))) { vlog_error("Error: clReleaseEvent failed! err: %d\n", error); goto exit; } // 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: clEnqueueMapBuffer failed! err: %d\n", error); goto exit; } // 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 = clSetKernelArg(kernel, 2, sizeof(tinfo->inBuf2), &tinfo->inBuf2))) { 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"); goto exit; } } // Get that moving if ((error = clFlush(tinfo->tQueue))) vlog("clFlush 2 failed\n"); if (gSkipCorrectnessTesting) return CL_SUCCESS; // Calculate the correctly rounded reference result r = (cl_double *)gOut_Ref + thread_id * buffer_elements; s = (cl_double *)gIn + thread_id * buffer_elements; s2 = (cl_double *)gIn2 + thread_id * buffer_elements; for (j = 0; j < buffer_elements; j++) r[j] = (cl_double)func.f_ff(s[j], s2[j]); // Read the data back -- no need to wait for the first N-1 buffers. This is // an in order queue. for (j = gMinVectorSizeIndex; j + 1 < gMaxVectorSizeIndex; j++) { out[j] = (cl_ulong *)clEnqueueMapBuffer( tinfo->tQueue, tinfo->outBuf[j], CL_FALSE, 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); goto exit; } } // Wait for the last buffer out[j] = (cl_ulong *)clEnqueueMapBuffer(tinfo->tQueue, tinfo->outBuf[j], CL_TRUE, 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); goto exit; } // Verify data t = (cl_ulong *)r; for (j = 0; j < buffer_elements; j++) { for (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_ff(s[j], s2[j]); float err = Bruteforce_Ulp_Error_Double(test, correct); int fail = !(fabsf(err) <= ulps); if (fail && ftz) { // retry per section 6.5.3.2 if (IsDoubleResultSubnormal(correct, ulps)) { fail = fail && (test != 0.0f); if (!fail) err = 0.0f; } // nextafter on FTZ platforms may return the smallest // normal float (2^-126) given a denormal or a zero // as the first argument. The rationale here is that // nextafter flushes the argument to zero and then // returns the next representable number in the // direction of the second argument, and since // denorms are considered as zero, the smallest // normal number is the next representable number. // In which case, it should have the same sign as the // second argument. if (isNextafter) { if (IsDoubleSubnormal(s[j]) || s[j] == 0.0f) { cl_double value = copysign(twoToMinus1022, s2[j]); fail = fail && (test != value); if (!fail) err = 0.0f; } } else { // retry per section 6.5.3.3 if (IsDoubleSubnormal(s[j])) { long double correct2 = func.f_ff(0.0, s2[j]); long double correct3 = func.f_ff(-0.0, s2[j]); 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; } // try with both args as zero if (IsDoubleSubnormal(s2[j])) { correct2 = func.f_ff(0.0, 0.0); correct3 = func.f_ff(-0.0, 0.0); long double correct4 = func.f_ff(0.0, -0.0); long double correct5 = func.f_ff(-0.0, -0.0); err2 = Bruteforce_Ulp_Error_Double(test, correct2); err3 = Bruteforce_Ulp_Error_Double(test, correct3); float err4 = Bruteforce_Ulp_Error_Double(test, correct4); float err5 = Bruteforce_Ulp_Error_Double(test, correct5); fail = fail && ((!(fabsf(err2) <= ulps)) && (!(fabsf(err3) <= ulps)) && (!(fabsf(err4) <= ulps)) && (!(fabsf(err5) <= ulps))); if (fabsf(err2) < fabsf(err)) err = err2; if (fabsf(err3) < fabsf(err)) err = err3; if (fabsf(err4) < fabsf(err)) err = err4; if (fabsf(err5) < fabsf(err)) err = err5; // retry per section 6.5.3.4 if (IsDoubleResultSubnormal(correct2, ulps) || IsDoubleResultSubnormal(correct3, ulps) || IsDoubleResultSubnormal(correct4, ulps) || IsDoubleResultSubnormal(correct5, ulps)) { fail = fail && (test != 0.0f); if (!fail) err = 0.0f; } } } else if (IsDoubleSubnormal(s2[j])) { long double correct2 = func.f_ff(s[j], 0.0); long double correct3 = func.f_ff(s[j], -0.0); 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]; tinfo->maxErrorValue2 = s2[j]; } if (fail) { vlog_error("\nERROR: %s%s: %f ulp error at {%.13la, " "%.13la}: *%.13la vs. %.13la\n", name, sizeNames[k], err, s[j], s2[j], r[j], test); error = -1; goto exit; } } } } for (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:%10zu buf_elements:%10u ulps:%5.3f " "ThreadCount:%2u\n", base, job->step, job->scale, buffer_elements, job->ulps, job->threadCount); } else { vlog("."); } fflush(stdout); } exit: return error; } int TestFunc_Float_Float_Float(const Func *f, MTdata d, bool relaxedMode) { return TestFunc_Float_Float_Float_common(f, d, 0, relaxedMode); } int TestFunc_Double_Double_Double(const Func *f, MTdata d, bool relaxedMode) { return TestFunc_Double_Double_Double_common(f, d, 0, relaxedMode); } int TestFunc_Float_Float_Float_nextafter(const Func *f, MTdata d, bool relaxedMode) { return TestFunc_Float_Float_Float_common(f, d, 1, relaxedMode); } int TestFunc_Double_Double_Double_nextafter(const Func *f, MTdata d, bool relaxedMode) { return TestFunc_Double_Double_Double_common(f, d, 1, relaxedMode); }