blob: a86277f1d910b060dc044fbad252d4ba66c3563e [file] [log] [blame]
//
// 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_Float2_Float(const Func *f, MTdata, bool relaxedMode);
int TestFunc_Double2_Double(const Func *f, MTdata, bool relaxedMode);
extern const vtbl _unary_two_results = { "unary_two_results",
TestFunc_Float2_Float,
TestFunc_Double2_Double };
static int BuildKernel(const char *name, int vectorSize, cl_kernel *k,
cl_program *p, bool relaxedMode);
static int BuildKernelDouble(const char *name, int vectorSize, cl_kernel *k,
cl_program *p, bool relaxedMode);
static int BuildKernel(const char *name, int vectorSize, 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], "* out2, __global float", sizeNames[vectorSize], "* in)\n"
"{\n"
" int i = get_global_id(0);\n"
" out[i] = ", name, "( in[i], out2 + i );\n"
"}\n"
};
const char *c3[] = { "__kernel void math_kernel", sizeNames[vectorSize], "( __global float* out, __global float* out2, __global float* in)\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 iout = NAN;\n"
" f0 = ", name, "( f0, &iout );\n"
" vstore3( f0, 0, out + 3*i );\n"
" vstore3( iout, 0, out2 + 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 iout = NAN;\n"
" float3 f0;\n"
" switch( parity )\n"
" {\n"
" case 1:\n"
" f0 = (float3)( in[3*i], NAN, NAN ); \n"
" break;\n"
" case 0:\n"
" f0 = (float3)( in[3*i], in[3*i+1], NAN ); \n"
" break;\n"
" }\n"
" f0 = ", name, "( f0, &iout );\n"
" switch( parity )\n"
" {\n"
" case 0:\n"
" out[3*i+1] = f0.y; \n"
" out2[3*i+1] = iout.y; \n"
" // fall through\n"
" case 1:\n"
" out[3*i] = f0.x; \n"
" out2[3*i] = iout.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 MakeKernel(kern, (cl_uint)kernSize, testName, k, p, relaxedMode);
}
static int BuildKernelDouble(const char *name, int vectorSize, 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], "* out2, __global double", sizeNames[vectorSize], "* in)\n"
"{\n"
" int i = get_global_id(0);\n"
" out[i] = ", name, "( in[i], out2 + 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* out2, __global double* in)\n"
"{\n"
" size_t i = get_global_id(0);\n"
" if( i + 1 < get_global_size(0) )\n"
" {\n"
" double3 f0 = vload3( 0, in + 3 * i );\n"
" double3 iout = NAN;\n"
" f0 = ", name, "( f0, &iout );\n"
" vstore3( f0, 0, out + 3*i );\n"
" vstore3( iout, 0, out2 + 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 iout = NAN;\n"
" double3 f0;\n"
" switch( parity )\n"
" {\n"
" case 1:\n"
" f0 = (double3)( in[3*i], NAN, NAN ); \n"
" break;\n"
" case 0:\n"
" f0 = (double3)( in[3*i], in[3*i+1], NAN ); \n"
" break;\n"
" }\n"
" f0 = ", name, "( f0, &iout );\n"
" switch( parity )\n"
" {\n"
" case 0:\n"
" out[3*i+1] = f0.y; \n"
" out2[3*i+1] = iout.y; \n"
" // fall through\n"
" case 1:\n"
" out[3*i] = f0.x; \n"
" out2[3*i] = iout.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 MakeKernel(kern, (cl_uint)kernSize, testName, k, p, relaxedMode);
}
typedef struct BuildKernelInfo
{
cl_uint offset; // the first vector size to build
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 );
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->kernels + i,
info->programs + i, info->relaxedMode);
}
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->kernels + i,
info->programs + i, info->relaxedMode);
}
int TestFunc_Float2_Float(const Func *f, MTdata d, bool relaxedMode)
{
uint64_t i;
uint32_t j, k;
uint32_t l;
int error;
char const * testing_mode;
cl_program programs[ VECTOR_SIZE_COUNT ];
cl_kernel kernels[ VECTOR_SIZE_COUNT ];
float maxError0 = 0.0f;
float maxError1 = 0.0f;
int ftz = f->ftz || gForceFTZ || 0 == (CL_FP_DENORM & gFloatCapabilities);
float maxErrorVal0 = 0.0f;
float maxErrorVal1 = 0.0f;
size_t bufferSize = (gWimpyMode)? gWimpyBufferSize: BUFFER_SIZE;
uint64_t step = bufferSize / sizeof( float );
int scale = (int)((1ULL<<32) / (16 * bufferSize / sizeof( float )) + 1);
cl_uchar overflow[BUFFER_SIZE / sizeof( float )];
int isFract = 0 == strcmp( "fract", f->nameInCode );
int skipNanInf = isFract && ! gInfNanSupport;
float float_ulps = getAllowedUlpError(f, relaxedMode);
logFunctionInfo(f->name, sizeof(cl_float), relaxedMode);
if( gWimpyMode )
{
step = (1ULL<<32) * gWimpyReductionFactor / (512);
}
// Init the kernels
BuildKernelInfo build_info = { gMinVectorSizeIndex, kernels, programs,
f->nameInCode, relaxedMode };
if( (error = ThreadPool_Do( BuildKernel_FloatFn, gMaxVectorSizeIndex - gMinVectorSizeIndex, &build_info ) ))
return error;
/*
for( i = gMinVectorSizeIndex; i < gMaxVectorSizeIndex; i++ )
if( (error = BuildKernel( f->nameInCode, (int) i, kernels + i, programs + i) ) )
return error;
*/
for( i = 0; i < (1ULL<<32); i += step )
{
//Init input array
uint32_t *p = (uint32_t *)gIn;
if( gWimpyMode )
{
for( j = 0; j < bufferSize / sizeof( float ); j++ )
{
p[j] = (uint32_t) i + j * scale;
if (relaxedMode && strcmp(f->name, "sincos") == 0)
{
float pj = *(float *)&p[j];
if (fabs(pj) > M_PI) ((float *)p)[j] = NAN;
}
}
}
else
{
for( j = 0; j < bufferSize / sizeof( float ); j++ )
{
p[j] = (uint32_t) i + j;
if (relaxedMode && strcmp(f->name, "sincos") == 0)
{
float pj = *(float *)&p[j];
if (fabs(pj) > M_PI) ((float *)p)[j] = NAN;
}
}
}
if( (error = clEnqueueWriteBuffer(gQueue, gInBuffer, CL_FALSE, 0, bufferSize, gIn, 0, NULL, NULL) ))
{
vlog_error( "\n*** Error %d in clEnqueueWriteBuffer ***\n", error );
return error;
}
// write garbage into output arrays
for( j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++ )
{
uint32_t pattern = 0xffffdead;
memset_pattern4(gOut[j], &pattern, bufferSize);
if( (error = clEnqueueWriteBuffer(gQueue, gOutBuffer[j], CL_FALSE, 0, bufferSize, gOut[j], 0, NULL, NULL) ))
{
vlog_error( "\n*** Error %d in clEnqueueWriteBuffer2(%d) ***\n", error, j );
goto exit;
}
memset_pattern4(gOut2[j], &pattern, bufferSize);
if( (error = clEnqueueWriteBuffer(gQueue, gOutBuffer2[j], CL_FALSE, 0, bufferSize, gOut2[j], 0, NULL, NULL)))
{
vlog_error( "\n*** Error %d in clEnqueueWriteBuffer2b(%d) ***\n", error, j );
goto exit;
}
}
// Run the kernels
for( j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++ )
{
size_t vectorSize = sizeValues[j] * sizeof(cl_float);
size_t localCount = (bufferSize + vectorSize - 1) / vectorSize;
if( ( error = clSetKernelArg(kernels[j], 0, sizeof( gOutBuffer[j] ), &gOutBuffer[j] ) )) { LogBuildError(programs[j]); goto exit; }
if( ( error = clSetKernelArg(kernels[j], 1, sizeof( gOutBuffer2[j] ), &gOutBuffer2[j] ) )) { LogBuildError(programs[j]); goto exit; }
if( ( error = clSetKernelArg(kernels[j], 2, sizeof( gInBuffer ), &gInBuffer ) )) { LogBuildError(programs[j]); goto exit; }
if( (error = clEnqueueNDRangeKernel(gQueue, kernels[j], 1, NULL, &localCount, NULL, 0, NULL, NULL)) )
{
vlog_error( "FAILED -- could not execute kernel\n" );
goto exit;
}
}
// Get that moving
if( (error = clFlush(gQueue) ))
vlog( "clFlush failed\n" );
FPU_mode_type oldMode;
RoundingMode oldRoundMode = kRoundToNearestEven;
if( isFract )
{
//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);
}
//Calculate the correctly rounded reference result
float *r = (float *)gOut_Ref;
float *r2 = (float *)gOut_Ref2;
float *s = (float *)gIn;
if( skipNanInf )
{
for( j = 0; j < bufferSize / sizeof( float ); j++ )
{
double dd;
feclearexcept(FE_OVERFLOW);
if (relaxedMode)
r[j] = (float) f->rfunc.f_fpf( s[j], &dd );
else
r[j] = (float) f->func.f_fpf( s[j], &dd );
r2[j] = (float) dd;
overflow[j] = FE_OVERFLOW == (FE_OVERFLOW & fetestexcept(FE_OVERFLOW));
}
}
else
{
for( j = 0; j < bufferSize / sizeof( float ); j++ )
{
double dd;
if (relaxedMode)
r[j] = (float)f->rfunc.f_fpf(s[j], &dd);
else
r[j] = (float) f->func.f_fpf( s[j], &dd );
r2[j] = (float) dd;
}
}
if( isFract && ftz )
RestoreFPState( &oldMode );
// Read the data back
for( j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++ )
{
if( (error = clEnqueueReadBuffer(gQueue, gOutBuffer[j], CL_TRUE, 0, bufferSize, gOut[j], 0, NULL, NULL)) )
{
vlog_error( "ReadArray failed %d\n", error );
goto exit;
}
if( (error = clEnqueueReadBuffer(gQueue, gOutBuffer2[j], CL_TRUE, 0, bufferSize, gOut2[j], 0, NULL, NULL)) )
{
vlog_error( "ReadArray2 failed %d\n", error );
goto exit;
}
}
if( gSkipCorrectnessTesting )
{
if (isFract && gIsInRTZMode)
(void)set_round(oldRoundMode, kfloat);
break;
}
//Verify data
uint32_t *t = (uint32_t *)gOut_Ref;
uint32_t *t2 = (uint32_t *)gOut_Ref2;
for( j = 0; j < bufferSize / sizeof( float ); j++ )
{
for( k = gMinVectorSizeIndex; k < gMaxVectorSizeIndex; k++ )
{
uint32_t *q = (uint32_t *)gOut[k];
uint32_t *q2 = (uint32_t *)gOut2[k];
// If we aren't getting the correctly rounded result
if( t[j] != q[j] || t2[j] != q2[j] )
{
double correct, correct2;
float err, err2;
float test = ((float*) q)[j];
float test2 = ((float*) q2)[j];
if (relaxedMode)
correct = f->rfunc.f_fpf(s[j], &correct2);
else
correct = f->func.f_fpf( s[j], &correct2 );
// Per section 10 paragraph 6, accept any result if an input or output is a infinity or NaN or overflow
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(correct2)|| IsFloatNaN(correct2) ||
IsFloatInfinity(s[j]) || IsFloatNaN(s[j]) )
continue;
}
typedef int (*CheckForSubnormal) (double,float); // If we are in fast relaxed math, we have a different calculation for the subnormal threshold.
CheckForSubnormal isFloatResultSubnormalPtr;
if (relaxedMode)
{
err = Abs_Error( test, correct);
err2 = Abs_Error( test2, correct2);
isFloatResultSubnormalPtr = &IsFloatResultSubnormalAbsError;
}
else
{
err = Ulp_Error( test, correct );
err2 = Ulp_Error( test2, correct2 );
isFloatResultSubnormalPtr = &IsFloatResultSubnormal;
}
int fail = ! (fabsf(err) <= float_ulps && fabsf(err2) <= float_ulps);
if( ftz )
{
// retry per section 6.5.3.2
if( (*isFloatResultSubnormalPtr)(correct, float_ulps) )
{
if( (*isFloatResultSubnormalPtr) (correct2, float_ulps ))
{
fail = fail && ! ( test == 0.0f && test2 == 0.0f );
if( ! fail )
{
err = 0.0f;
err2 = 0.0f;
}
}
else
{
fail = fail && ! ( test == 0.0f && fabsf(err2) <= float_ulps);
if( ! fail )
err = 0.0f;
}
}
else if( (*isFloatResultSubnormalPtr)(correct2, float_ulps ) )
{
fail = fail && ! ( test2 == 0.0f && fabsf(err) <= float_ulps);
if( ! fail )
err2 = 0.0f;
}
// retry per section 6.5.3.3
if( IsFloatSubnormal( s[j] ) )
{
double correctp, correctn;
double correct2p, correct2n;
float errp, err2p, errn, err2n;
if( skipNanInf )
feclearexcept(FE_OVERFLOW);
if (relaxedMode)
{
correctp = f->rfunc.f_fpf( 0.0, &correct2p );
correctn = f->rfunc.f_fpf( -0.0, &correct2n );
}
else
{
correctp = f->func.f_fpf( 0.0, &correct2p );
correctn = f->func.f_fpf( -0.0, &correct2n );
}
// Per section 10 paragraph 6, accept any result if an input or output is a infinity or NaN or overflow
if( skipNanInf )
{
if( fetestexcept(FE_OVERFLOW) )
continue;
// Note: no double rounding here. Reference functions calculate in single precision.
if( IsFloatInfinity(correctp) || IsFloatNaN(correctp) ||
IsFloatInfinity(correctn) || IsFloatNaN(correctn) ||
IsFloatInfinity(correct2p) || IsFloatNaN(correct2p) ||
IsFloatInfinity(correct2n) || IsFloatNaN(correct2n) )
continue;
}
if (relaxedMode)
{
errp = Abs_Error( test, correctp );
err2p = Abs_Error( test, correct2p );
errn = Abs_Error( test, correctn );
err2n = Abs_Error( test, correct2n );
}
else
{
errp = Ulp_Error( test, correctp );
err2p = Ulp_Error( test, correct2p );
errn = Ulp_Error( test, correctn );
err2n = Ulp_Error( test, correct2n );
}
fail = fail && ((!(fabsf(errp) <= float_ulps)) && (!(fabsf(err2p) <= float_ulps)) &&
((!(fabsf(errn) <= float_ulps)) && (!(fabsf(err2n) <= float_ulps))) );
if( fabsf( errp ) < fabsf(err ) )
err = errp;
if( fabsf( errn ) < fabsf(err ) )
err = errn;
if( fabsf( err2p ) < fabsf(err2 ) )
err2 = err2p;
if( fabsf( err2n ) < fabsf(err2 ) )
err2 = err2n;
// retry per section 6.5.3.4
if( (*isFloatResultSubnormalPtr)( correctp, float_ulps ) || (*isFloatResultSubnormalPtr)( correctn, float_ulps ) )
{
if( (*isFloatResultSubnormalPtr)( correct2p, float_ulps ) || (*isFloatResultSubnormalPtr)( correct2n, float_ulps ) )
{
fail = fail && !( test == 0.0f && test2 == 0.0f);
if( ! fail )
err = err2 = 0.0f;
}
else
{
fail = fail && ! (test == 0.0f && fabsf(err2) <= float_ulps);
if( ! fail )
err = 0.0f;
}
}
else if( (*isFloatResultSubnormalPtr)( correct2p, float_ulps ) || (*isFloatResultSubnormalPtr)( correct2n, float_ulps ) )
{
fail = fail && ! (test2 == 0.0f && (fabsf(err) <= float_ulps));
if( ! fail )
err2 = 0.0f;
}
}
}
if( fabsf(err ) > maxError0 )
{
maxError0 = fabsf(err);
maxErrorVal0 = s[j];
}
if( fabsf(err2 ) > maxError1 )
{
maxError1 = fabsf(err2);
maxErrorVal1 = s[j];
}
if( fail )
{
vlog_error( "\nERROR: %s%s: {%f, %f} ulp error at %a: *{%a, %a} vs. {%a, %a}\n", f->name, sizeNames[k], err, err2, ((float*) gIn)[j], ((float*) gOut_Ref)[j], ((float*) gOut_Ref2)[j], test, test2 );
error = -1;
goto exit;
}
}
}
}
if (isFract && gIsInRTZMode)
(void)set_round(oldRoundMode, kfloat);
if( 0 == (i & 0x0fffffff) )
{
if (gVerboseBruteForce)
{
vlog("base:%14u step:%10zu bufferSize:%10zd \n", i, step, bufferSize);
} else
{
vlog(".");
}
fflush(stdout);
}
}
if( ! gSkipCorrectnessTesting )
{
if( gWimpyMode )
vlog( "Wimp pass" );
else
vlog( "passed" );
}
if( gMeasureTimes )
{
//Init input array
uint32_t *p = (uint32_t *)gIn;
for( j = 0; j < bufferSize / sizeof( float ); j++ )
p[j] = genrand_int32(d);
if( (error = clEnqueueWriteBuffer(gQueue, gInBuffer, CL_FALSE, 0, bufferSize, gIn, 0, NULL, NULL) ))
{
vlog_error( "\n*** Error %d in clEnqueueWriteBuffer ***\n", error );
return error;
}
// Run the kernels
for( j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++ )
{
size_t vectorSize = sizeValues[j] * sizeof(cl_float);
size_t localCount = (bufferSize + vectorSize - 1) / vectorSize;
if( ( error = clSetKernelArg(kernels[j], 0, sizeof( gOutBuffer[j] ), &gOutBuffer[j] ) )) { LogBuildError(programs[j]); goto exit; }
if( ( error = clSetKernelArg(kernels[j], 1, sizeof( gOutBuffer2[j] ), &gOutBuffer2[j]) )) { LogBuildError(programs[j]); goto exit; }
if( ( error = clSetKernelArg( kernels[j], 2, sizeof( gInBuffer ), &gInBuffer ) )) { LogBuildError(programs[j]); goto exit; }
double sum = 0.0;
double bestTime = INFINITY;
for( k = 0; k < PERF_LOOP_COUNT; k++ )
{
uint64_t startTime = GetTime();
if( (error = clEnqueueNDRangeKernel(gQueue, kernels[j], 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 / (bufferSize / sizeof( float ) );
vlog_perf( clocksPerOp, LOWER_IS_BETTER, "clocks / element", "%sf%s", f->name, sizeNames[j] );
}
}
if( ! gSkipCorrectnessTesting )
vlog( "\t{%8.2f, %8.2f} @ {%a, %a}", maxError0, maxError1, maxErrorVal0, maxErrorVal1 );
vlog( "\n" );
exit:
// Release
for( k = gMinVectorSizeIndex; k < gMaxVectorSizeIndex; k++ )
{
clReleaseKernel(kernels[k]);
clReleaseProgram(programs[k]);
}
return error;
}
int TestFunc_Double2_Double(const Func *f, MTdata d, bool relaxedMode)
{
uint64_t i;
uint32_t j, k;
int error;
cl_program programs[ VECTOR_SIZE_COUNT ];
cl_kernel kernels[ VECTOR_SIZE_COUNT ];
float maxError0 = 0.0f;
float maxError1 = 0.0f;
int ftz = f->ftz || gForceFTZ;
double maxErrorVal0 = 0.0f;
double maxErrorVal1 = 0.0f;
size_t bufferSize = (gWimpyMode)? gWimpyBufferSize: BUFFER_SIZE;
uint64_t step = bufferSize / sizeof( cl_double );
int scale = (int)((1ULL<<32) / (16 * bufferSize / sizeof( cl_double )) + 1);
logFunctionInfo(f->name, sizeof(cl_double), relaxedMode);
if( gWimpyMode )
{
step = (1ULL<<32) * gWimpyReductionFactor / (512);
}
Force64BitFPUPrecision();
// Init the kernels
BuildKernelInfo build_info = { gMinVectorSizeIndex, kernels, programs,
f->nameInCode, relaxedMode };
if( (error = ThreadPool_Do( BuildKernel_DoubleFn,
gMaxVectorSizeIndex - gMinVectorSizeIndex,
&build_info ) ))
{
return error;
}
/*
for( i = gMinVectorSizeIndex; i < gMaxVectorSizeIndex; i++ )
if( (error = BuildKernelDouble( f->nameInCode, (int) i, kernels + i, programs + i) ) )
return error;
*/
for( i = 0; i < (1ULL<<32); i += step )
{
//Init input array
double *p = (double *)gIn;
if( gWimpyMode )
{
for( j = 0; j < bufferSize / sizeof( cl_double ); j++ )
p[j] = DoubleFromUInt32((uint32_t) i + j * scale);
}
else
{
for( j = 0; j < bufferSize / sizeof( cl_double ); j++ )
p[j] = DoubleFromUInt32((uint32_t) i + j);
}
if( (error = clEnqueueWriteBuffer(gQueue, gInBuffer, CL_FALSE, 0, bufferSize, gIn, 0, NULL, NULL) ))
{
vlog_error( "\n*** Error %d in clEnqueueWriteBuffer ***\n", error );
return error;
}
// write garbage into output arrays
for( j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++ )
{
uint32_t pattern = 0xffffdead;
memset_pattern4(gOut[j], &pattern, bufferSize);
if( (error = clEnqueueWriteBuffer(gQueue, gOutBuffer[j], CL_FALSE, 0, bufferSize, gOut[j], 0, NULL, NULL) ))
{
vlog_error( "\n*** Error %d in clEnqueueWriteBuffer2(%d) ***\n", error, j );
goto exit;
}
memset_pattern4(gOut2[j], &pattern, bufferSize);
if( (error = clEnqueueWriteBuffer(gQueue, gOutBuffer2[j], CL_FALSE, 0, bufferSize, gOut2[j], 0, NULL, NULL)))
{
vlog_error( "\n*** Error %d in clEnqueueWriteBuffer2b(%d) ***\n", error, j );
goto exit;
}
}
// Run the kernels
for( j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++ )
{
size_t vectorSize = sizeValues[j] * sizeof(cl_double);
size_t localCount = (bufferSize + vectorSize - 1) / vectorSize;
if( ( error = clSetKernelArg(kernels[j], 0, sizeof( gOutBuffer[j] ), &gOutBuffer[j] ) )) { LogBuildError(programs[j]); goto exit; }
if( ( error = clSetKernelArg(kernels[j], 1, sizeof( gOutBuffer2[j] ), &gOutBuffer2[j] ) )) { LogBuildError(programs[j]); goto exit; }
if( ( error = clSetKernelArg(kernels[j], 2, sizeof( gInBuffer ), &gInBuffer ) )) { LogBuildError(programs[j]); goto exit; }
if( (error = clEnqueueNDRangeKernel(gQueue, kernels[j], 1, NULL, &localCount, NULL, 0, NULL, NULL)) )
{
vlog_error( "FAILED -- could not execute kernel\n" );
goto exit;
}
}
// Get that moving
if( (error = clFlush(gQueue) ))
vlog( "clFlush failed\n" );
//Calculate the correctly rounded reference result
double *r = (double *)gOut_Ref;
double *r2 = (double *)gOut_Ref2;
double *s = (double *)gIn;
for( j = 0; j < bufferSize / sizeof( cl_double ); j++ )
{
long double dd;
r[j] = (double) f->dfunc.f_fpf( s[j], &dd );
r2[j] = (double) dd;
}
// Read the data back
for( j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++ )
{
if( (error = clEnqueueReadBuffer(gQueue, gOutBuffer[j], CL_TRUE, 0, bufferSize, gOut[j], 0, NULL, NULL)) )
{
vlog_error( "ReadArray failed %d\n", error );
goto exit;
}
if( (error = clEnqueueReadBuffer(gQueue, gOutBuffer2[j], CL_TRUE, 0, bufferSize, gOut2[j], 0, NULL, NULL)) )
{
vlog_error( "ReadArray2 failed %d\n", error );
goto exit;
}
}
if( gSkipCorrectnessTesting )
break;
//Verify data
uint64_t *t = (uint64_t *)gOut_Ref;
uint64_t *t2 = (uint64_t *)gOut_Ref2;
for( j = 0; j < bufferSize / sizeof( double ); j++ )
{
for( k = gMinVectorSizeIndex; k < gMaxVectorSizeIndex; k++ )
{
uint64_t *q = (uint64_t *)(gOut[k]);
uint64_t *q2 = (uint64_t *)(gOut2[k]);
// If we aren't getting the correctly rounded result
if( t[j] != q[j] || t2[j] != q2[j] )
{
double test = ((double*) q)[j];
double test2 = ((double*) q2)[j];
long double correct2;
long double correct = f->dfunc.f_fpf( s[j], &correct2 );
float err = Bruteforce_Ulp_Error_Double( test, correct );
float err2 = Bruteforce_Ulp_Error_Double( test2, correct2 );
int fail = ! (fabsf(err) <= f->double_ulps && fabsf(err2) <= f->double_ulps);
if( ftz )
{
// retry per section 6.5.3.2
if( IsDoubleResultSubnormal(correct, f->double_ulps ) )
{
if( IsDoubleResultSubnormal( correct2, f->double_ulps ) )
{
fail = fail && ! ( test == 0.0f && test2 == 0.0f );
if( ! fail )
{
err = 0.0f;
err2 = 0.0f;
}
}
else
{
fail = fail && ! ( test == 0.0f && fabsf(err2) <= f->double_ulps);
if( ! fail )
err = 0.0f;
}
}
else if( IsDoubleResultSubnormal( correct2, f->double_ulps ) )
{
fail = fail && ! ( test2 == 0.0f && fabsf(err) <= f->double_ulps);
if( ! fail )
err2 = 0.0f;
}
// retry per section 6.5.3.3
if( IsDoubleSubnormal( s[j] ) )
{
long double correct2p, correct2n;
long double correctp = f->dfunc.f_fpf( 0.0, &correct2p );
long double correctn = f->dfunc.f_fpf( -0.0, &correct2n );
float errp = Bruteforce_Ulp_Error_Double( test, correctp );
float err2p = Bruteforce_Ulp_Error_Double( test, correct2p );
float errn = Bruteforce_Ulp_Error_Double( test, correctn );
float err2n = Bruteforce_Ulp_Error_Double( test, correct2n );
fail = fail && ((!(fabsf(errp) <= f->double_ulps)) && (!(fabsf(err2p) <= f->double_ulps)) &&
((!(fabsf(errn) <= f->double_ulps)) && (!(fabsf(err2n) <= f->double_ulps))) );
if( fabsf( errp ) < fabsf(err ) )
err = errp;
if( fabsf( errn ) < fabsf(err ) )
err = errn;
if( fabsf( err2p ) < fabsf(err2 ) )
err2 = err2p;
if( fabsf( err2n ) < fabsf(err2 ) )
err2 = err2n;
// retry per section 6.5.3.4
if( IsDoubleResultSubnormal( correctp, f->double_ulps ) || IsDoubleResultSubnormal( correctn, f->double_ulps ) )
{
if( IsDoubleResultSubnormal( correct2p, f->double_ulps ) || IsDoubleResultSubnormal( correct2n, f->double_ulps ) )
{
fail = fail && !( test == 0.0f && test2 == 0.0f);
if( ! fail )
err = err2 = 0.0f;
}
else
{
fail = fail && ! (test == 0.0f && fabsf(err2) <= f->double_ulps);
if( ! fail )
err = 0.0f;
}
}
else if( IsDoubleResultSubnormal( correct2p, f->double_ulps ) || IsDoubleResultSubnormal( correct2n, f->double_ulps ) )
{
fail = fail && ! (test2 == 0.0f && (fabsf(err) <= f->double_ulps));
if( ! fail )
err2 = 0.0f;
}
}
}
if( fabsf(err ) > maxError0 )
{
maxError0 = fabsf(err);
maxErrorVal0 = s[j];
}
if( fabsf(err2 ) > maxError1 )
{
maxError1 = fabsf(err2);
maxErrorVal1 = s[j];
}
if( fail )
{
vlog_error( "\nERROR: %sD%s: {%f, %f} ulp error at %.13la: *{%.13la, %.13la} vs. {%.13la, %.13la}\n", f->name, sizeNames[k], err, err2, ((double*) gIn)[j], ((double*) gOut_Ref)[j], ((double*) gOut_Ref2)[j], test, test2 );
error = -1;
goto exit;
}
}
}
}
if( 0 == (i & 0x0fffffff) )
{
if (gVerboseBruteForce)
{
vlog("base:%14u step:%10zu bufferSize:%10zd \n", i, step, bufferSize);
} else
{
vlog("." );
}
fflush(stdout);
}
}
if( ! gSkipCorrectnessTesting )
{
if( gWimpyMode )
vlog( "Wimp pass" );
else
vlog( "passed" );
}
if( gMeasureTimes )
{
//Init input array
double *p = (double*) gIn;
for( j = 0; j < bufferSize / sizeof( double ); j++ )
p[j] = DoubleFromUInt32(genrand_int32(d) );
if( (error = clEnqueueWriteBuffer(gQueue, gInBuffer, CL_FALSE, 0, bufferSize, gIn, 0, NULL, NULL) ))
{
vlog_error( "\n*** Error %d in clEnqueueWriteBuffer ***\n", error );
return error;
}
// Run the kernels
for( j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++ )
{
size_t vectorSize = sizeValues[j] * sizeof(cl_double);
size_t localCount = (bufferSize + vectorSize - 1) / vectorSize;
if( ( error = clSetKernelArg(kernels[j], 0, sizeof( gOutBuffer[j] ), &gOutBuffer[j] ) )) { LogBuildError(programs[j]); goto exit; }
if( ( error = clSetKernelArg(kernels[j], 1, sizeof( gOutBuffer2[j] ), &gOutBuffer2[j]) )) { LogBuildError(programs[j]); goto exit; }
if( ( error = clSetKernelArg( kernels[j], 2, sizeof( gInBuffer ), &gInBuffer ) )) { LogBuildError(programs[j]); goto exit; }
double sum = 0.0;
double bestTime = INFINITY;
for( k = 0; k < PERF_LOOP_COUNT; k++ )
{
uint64_t startTime = GetTime();
if( (error = clEnqueueNDRangeKernel(gQueue, kernels[j], 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 / (bufferSize / 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, %8.2f} @ {%a, %a}", maxError0, maxError1, maxErrorVal0, maxErrorVal1 );
vlog( "\n" );
exit:
// Release
for( k = gMinVectorSizeIndex; k < gMaxVectorSizeIndex; k++ )
{
clReleaseKernel(kernels[k]);
clReleaseProgram(programs[k]);
}
return error;
}