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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 "common.h"
#include "function_list.h"
#include "test_functions.h"
#include "utility.h"
#include <cstring>
namespace {
cl_int BuildKernelFn(cl_uint job_id, cl_uint thread_id UNUSED, void *p)
{
BuildKernelInfo &info = *(BuildKernelInfo *)p;
auto generator = [](const std::string &kernel_name, const char *builtin,
cl_uint vector_size_index) {
return GetTernaryKernel(kernel_name, builtin, ParameterType::Double,
ParameterType::Double, ParameterType::Double,
ParameterType::Double, vector_size_index);
};
return BuildKernels(info, job_id, generator);
}
} // anonymous namespace
int TestFunc_mad_Double(const Func *f, MTdata d, bool relaxedMode)
{
int error;
Programs programs;
const unsigned thread_id = 0; // Test is currently not multithreaded.
KernelMatrix kernels;
float maxError = 0.0f;
double maxErrorVal = 0.0f;
double maxErrorVal2 = 0.0f;
double maxErrorVal3 = 0.0f;
uint64_t step = getTestStep(sizeof(double), BUFFER_SIZE);
logFunctionInfo(f->name, sizeof(cl_double), relaxedMode);
// Init the kernels
BuildKernelInfo build_info{ 1, kernels, programs, f->nameInCode,
relaxedMode };
if ((error = ThreadPool_Do(BuildKernelFn,
gMaxVectorSizeIndex - gMinVectorSizeIndex,
&build_info)))
return error;
for (uint64_t i = 0; i < (1ULL << 32); i += step)
{
// Init input array
double *p = (double *)gIn;
double *p2 = (double *)gIn2;
double *p3 = (double *)gIn3;
for (size_t j = 0; j < BUFFER_SIZE / sizeof(double); j++)
{
p[j] = DoubleFromUInt32(genrand_int32(d));
p2[j] = DoubleFromUInt32(genrand_int32(d));
p3[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;
}
if ((error = clEnqueueWriteBuffer(gQueue, gInBuffer3, CL_FALSE, 0,
BUFFER_SIZE, gIn3, 0, NULL, NULL)))
{
vlog_error("\n*** Error %d in clEnqueueWriteBuffer3 ***\n", error);
return error;
}
// Write garbage into output arrays
for (auto j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++)
{
uint32_t pattern = 0xffffdead;
if (gHostFill)
{
memset_pattern4(gOut[j], &pattern, BUFFER_SIZE);
if ((error = clEnqueueWriteBuffer(gQueue, gOutBuffer[j],
CL_FALSE, 0, BUFFER_SIZE,
gOut[j], 0, NULL, NULL)))
{
vlog_error(
"\n*** Error %d in clEnqueueWriteBuffer2(%d) ***\n",
error, j);
return error;
}
}
else
{
if ((error = clEnqueueFillBuffer(gQueue, gOutBuffer[j],
&pattern, sizeof(pattern), 0,
BUFFER_SIZE, 0, NULL, NULL)))
{
vlog_error("Error: clEnqueueFillBuffer failed! err: %d\n",
error);
return error;
}
}
}
// Run the kernels
for (auto 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(kernels[j][thread_id], 0,
sizeof(gOutBuffer[j]), &gOutBuffer[j])))
{
LogBuildError(programs[j]);
return error;
}
if ((error = clSetKernelArg(kernels[j][thread_id], 1,
sizeof(gInBuffer), &gInBuffer)))
{
LogBuildError(programs[j]);
return error;
}
if ((error = clSetKernelArg(kernels[j][thread_id], 2,
sizeof(gInBuffer2), &gInBuffer2)))
{
LogBuildError(programs[j]);
return error;
}
if ((error = clSetKernelArg(kernels[j][thread_id], 3,
sizeof(gInBuffer3), &gInBuffer3)))
{
LogBuildError(programs[j]);
return error;
}
if ((error = clEnqueueNDRangeKernel(gQueue, kernels[j][thread_id],
1, NULL, &localCount, NULL, 0,
NULL, NULL)))
{
vlog_error("FAILED -- could not execute kernel\n");
return error;
}
}
// Get that moving
if ((error = clFlush(gQueue))) vlog("clFlush failed\n");
// Calculate the correctly rounded reference result
double *r = (double *)gOut_Ref;
double *s = (double *)gIn;
double *s2 = (double *)gIn2;
double *s3 = (double *)gIn3;
for (size_t j = 0; j < BUFFER_SIZE / sizeof(double); j++)
r[j] = (double)f->dfunc.f_fff(s[j], s2[j], s3[j]);
// Read the data back
for (auto j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++)
{
if ((error =
clEnqueueReadBuffer(gQueue, gOutBuffer[j], CL_TRUE, 0,
BUFFER_SIZE, gOut[j], 0, NULL, NULL)))
{
vlog_error("ReadArray failed %d\n", error);
return error;
}
}
if (gSkipCorrectnessTesting) break;
// Verify data -- No verification possible.
// MAD is a random number generator.
if (0 == (i & 0x0fffffff))
{
vlog(".");
fflush(stdout);
}
}
if (!gSkipCorrectnessTesting)
{
if (gWimpyMode)
vlog("Wimp pass");
else
vlog("passed");
vlog("\t%8.2f @ {%a, %a, %a}", maxError, maxErrorVal, maxErrorVal2,
maxErrorVal3);
}
vlog("\n");
return CL_SUCCESS;
}
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