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OpenCL-CTS/test_conformance/math_brute_force/binary.cpp
James Price 40f50d77a3 Rename test .c sources to .cpp where necessary (#604) 
Remove hacks to force language from CMake files.

Closes KhronosGroup/OpenCL-CTS#25
2020-02-21 17:34:31 +00:00

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//
// 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 <string.h>
#include "FunctionList.h"
int TestFunc_Float_Float_Float(const Func *f, MTdata);
int TestFunc_Double_Double_Double(const Func *f, MTdata);
int TestFunc_Float_Float_Float_nextafter(const Func *f, MTdata);
int TestFunc_Double_Double_Double_nextafter(const Func *f, MTdata);
int TestFunc_Float_Float_Float_common(const Func *f, MTdata, int isNextafter);
int TestFunc_Double_Double_Double_common(const Func *f, MTdata, int isNextafter);
const float twoToMinus126 = MAKE_HEX_FLOAT(0x1p-126f, 1, -126);
const double twoToMinus1022 = MAKE_HEX_DOUBLE(0x1p-1022, 1, -1022);
#if defined( __cplusplus )
extern "C"
#endif
const vtbl _binary = { "binary", TestFunc_Float_Float_Float, TestFunc_Double_Double_Double };
#if defined( __cplusplus )
extern "C"
#endif
const vtbl _binary_nextafter = { "binary_nextafter", TestFunc_Float_Float_Float_nextafter, TestFunc_Double_Double_Double_nextafter };
static int BuildKernel( const char *name, int vectorSize, cl_uint kernel_count, cl_kernel *k, cl_program *p );
static int BuildKernel( const char *name, int vectorSize, cl_uint kernel_count, cl_kernel *k, cl_program *p )
{
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"
" int 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, 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);
}
static int BuildKernelDouble( const char *name, int vectorSize, cl_uint kernel_count, cl_kernel *k, cl_program *p )
{
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"
" int 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, 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);
}
// 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 size_t specialValuesFloatCount = sizeof( specialValuesFloat ) / sizeof( specialValuesFloat[0] );
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;
}BuildKernelInfo;
static cl_int BuildKernel_FloatFn( cl_uint job_id, cl_uint thread_id UNUSED, void *p );
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 );
}
static cl_int BuildKernel_DoubleFn( cl_uint job_id, cl_uint thread_id UNUSED, void *p );
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 );
}
//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;
}TestInfo;
static cl_int TestFloat( cl_uint job_id, cl_uint thread_id, void *p );
int TestFunc_Float_Float_Float_common(const Func *f, MTdata d, int isNextafter)
{
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),gTestFastRelaxed);
// 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 = 1;
if (gWimpyMode){
test_info.subBufferSize = gWimpyBufferSize / (sizeof( cl_float) * RoundUpToNextPowerOfTwo(test_info.threadCount));
test_info.scale = (cl_uint) sizeof(cl_float) * 2 * gWimpyReductionFactor;
}
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.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, &region, &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, &region, &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, &region, &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 };
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
uint32_t *p = (uint32_t *)gIn;
uint32_t *p2 = (uint32_t *)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;
float ulps = job->ulps;
fptr func = job->f->func;
int ftz = job->ftz;
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;
float *r=0,*s=0,*s2=0;
cl_int copysign_test = 0;
RoundingMode oldRoundMode;
int skipVerification = 0;
if(gTestFastRelaxed)
{
if (strcmp(name,"pow")==0 && gFastRelaxedDerived)
{
func = job->f->rfunc;
ulps = INFINITY;
skipVerification = 1;
}else
{
func = job->f->rfunc;
ulps = job->f->relaxed_error;
}
}
// 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];
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 ( gTestFastRelaxed || 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( gTestFastRelaxed || 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( gTestFastRelaxed || 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 ( gTestFastRelaxed || 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 );
int TestFunc_Double_Double_Double_common(const Func *f, MTdata d, int isNextafter)
{
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),gTestFastRelaxed);
// 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 = 1;
if (gWimpyMode){
test_info.subBufferSize = gWimpyBufferSize / (sizeof( cl_double) * RoundUpToNextPowerOfTwo(test_info.threadCount));
test_info.scale = (cl_uint) sizeof(cl_double) * 2 * gWimpyReductionFactor;
}
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, &region, &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, &region, &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, &region, &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 };
if( (error = ThreadPool_Do( BuildKernel_DoubleFn, gMaxVectorSizeIndex - gMinVectorSizeIndex, &build_info ) ))
goto exit;
}
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,*s,*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)
{
return TestFunc_Float_Float_Float_common(f, d, 0);
}
int TestFunc_Double_Double_Double(const Func *f, MTdata d)
{
return TestFunc_Double_Double_Double_common(f, d, 0);
}
int TestFunc_Float_Float_Float_nextafter(const Func *f, MTdata d)
{
return TestFunc_Float_Float_Float_common(f, d, 1);
}
int TestFunc_Double_Double_Double_nextafter(const Func *f, MTdata d)
{
return TestFunc_Double_Double_Double_common(f, d, 1);
}
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