mirror of
https://github.com/KhronosGroup/OpenCL-CTS.git
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gWimpyBufferSize is never modified and is actually not used to modify the number of tests -- gWimpyReductionFactor is used for that purpose by some tests, but not all. This patch removes this unnecessary global variable to simplify the codebase, and reduce differences between tests. Signed-off-by: Marco Antognini <marco.antognini@arm.com>
730 lines
25 KiB
C++
730 lines
25 KiB
C++
//
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// Copyright (c) 2017 The Khronos Group Inc.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//
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#include "function_list.h"
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#include "test_functions.h"
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#include "utility.h"
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#include <cstring>
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static int BuildKernel(const char *name, int vectorSize, cl_uint kernel_count,
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cl_kernel *k, cl_program *p, bool relaxedMode)
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{
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const char *c[] = { "__kernel void math_kernel",
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sizeNames[vectorSize],
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"( __global float",
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sizeNames[vectorSize],
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"* out, __global float",
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sizeNames[vectorSize],
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"* in )\n"
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"{\n"
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" size_t i = get_global_id(0);\n"
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" out[i] = ",
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name,
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"( in[i] );\n"
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"}\n" };
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const char *c3[] = {
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"__kernel void math_kernel",
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sizeNames[vectorSize],
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"( __global float* out, __global float* in)\n"
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"{\n"
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" size_t i = get_global_id(0);\n"
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" if( i + 1 < get_global_size(0) )\n"
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" {\n"
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" float3 f0 = vload3( 0, in + 3 * i );\n"
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" f0 = ",
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name,
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"( f0 );\n"
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" vstore3( f0, 0, out + 3*i );\n"
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" }\n"
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" else\n"
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" {\n"
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" size_t parity = i & 1; // Figure out how many elements are "
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"left over after BUFFER_SIZE % (3*sizeof(float)). Assume power of two "
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"buffer size \n"
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" float3 f0;\n"
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" switch( parity )\n"
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" {\n"
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" case 1:\n"
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" f0 = (float3)( in[3*i], NAN, NAN ); \n"
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" break;\n"
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" case 0:\n"
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" f0 = (float3)( in[3*i], in[3*i+1], NAN ); \n"
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" break;\n"
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" }\n"
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" f0 = ",
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name,
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"( f0 );\n"
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" switch( parity )\n"
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" {\n"
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" case 0:\n"
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" out[3*i+1] = f0.y; \n"
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" // fall through\n"
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" case 1:\n"
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" out[3*i] = f0.x; \n"
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" break;\n"
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" }\n"
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" }\n"
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"}\n"
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};
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const char **kern = c;
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size_t kernSize = sizeof(c) / sizeof(c[0]);
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if (sizeValues[vectorSize] == 3)
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{
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kern = c3;
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kernSize = sizeof(c3) / sizeof(c3[0]);
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}
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char testName[32];
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snprintf(testName, sizeof(testName) - 1, "math_kernel%s",
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sizeNames[vectorSize]);
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return MakeKernels(kern, (cl_uint)kernSize, testName, kernel_count, k, p,
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relaxedMode);
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}
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typedef struct BuildKernelInfo
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{
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cl_uint offset; // the first vector size to build
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cl_uint kernel_count;
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cl_kernel **kernels;
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cl_program *programs;
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const char *nameInCode;
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bool relaxedMode; // Whether to build with -cl-fast-relaxed-math.
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} BuildKernelInfo;
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static cl_int BuildKernelFn(cl_uint job_id, cl_uint thread_id UNUSED, void *p)
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{
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BuildKernelInfo *info = (BuildKernelInfo *)p;
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cl_uint i = info->offset + job_id;
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return BuildKernel(info->nameInCode, i, info->kernel_count,
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info->kernels[i], info->programs + i, info->relaxedMode);
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}
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// Thread specific data for a worker thread
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typedef struct ThreadInfo
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{
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cl_mem inBuf; // input buffer for the thread
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cl_mem outBuf[VECTOR_SIZE_COUNT]; // output buffers for the thread
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float maxError; // max error value. Init to 0.
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double maxErrorValue; // position of the max error value. Init to 0.
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cl_command_queue tQueue; // per thread command queue to improve performance
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} ThreadInfo;
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typedef struct TestInfo
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{
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size_t subBufferSize; // Size of the sub-buffer in elements
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const Func *f; // A pointer to the function info
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cl_program programs[VECTOR_SIZE_COUNT]; // programs for various vector sizes
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cl_kernel
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*k[VECTOR_SIZE_COUNT]; // arrays of thread-specific kernels for each
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// worker thread: k[vector_size][thread_id]
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ThreadInfo *
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tinfo; // An array of thread specific information for each worker thread
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cl_uint threadCount; // Number of worker threads
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cl_uint jobCount; // Number of jobs
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cl_uint step; // step between each chunk and the next.
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cl_uint scale; // stride between individual test values
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float ulps; // max_allowed ulps
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int ftz; // non-zero if running in flush to zero mode
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int isRangeLimited; // 1 if the function is only to be evaluated over a
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// range
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float half_sin_cos_tan_limit;
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bool relaxedMode; // True if test is running in relaxed mode, false
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// otherwise.
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} TestInfo;
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static cl_int Test(cl_uint job_id, cl_uint thread_id, void *data);
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int TestFunc_Float_Float(const Func *f, MTdata d, bool relaxedMode)
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{
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TestInfo test_info;
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cl_int error;
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size_t i, j;
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float maxError = 0.0f;
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double maxErrorVal = 0.0;
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int skipTestingRelaxed = (relaxedMode && strcmp(f->name, "tan") == 0);
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logFunctionInfo(f->name, sizeof(cl_float), relaxedMode);
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// Init test_info
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memset(&test_info, 0, sizeof(test_info));
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test_info.threadCount = GetThreadCount();
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test_info.subBufferSize = BUFFER_SIZE
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/ (sizeof(cl_float) * RoundUpToNextPowerOfTwo(test_info.threadCount));
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test_info.scale = getTestScale(sizeof(cl_float));
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test_info.step = (cl_uint)test_info.subBufferSize * test_info.scale;
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if (test_info.step / test_info.subBufferSize != test_info.scale)
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{
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// there was overflow
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test_info.jobCount = 1;
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}
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else
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{
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test_info.jobCount = (cl_uint)((1ULL << 32) / test_info.step);
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}
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test_info.f = f;
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test_info.ulps = gIsEmbedded ? f->float_embedded_ulps : f->float_ulps;
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test_info.ftz =
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f->ftz || gForceFTZ || 0 == (CL_FP_DENORM & gFloatCapabilities);
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test_info.relaxedMode = relaxedMode;
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// cl_kernels aren't thread safe, so we make one for each vector size for
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// every thread
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for (i = gMinVectorSizeIndex; i < gMaxVectorSizeIndex; i++)
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{
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size_t array_size = test_info.threadCount * sizeof(cl_kernel);
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test_info.k[i] = (cl_kernel *)malloc(array_size);
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if (NULL == test_info.k[i])
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{
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vlog_error("Error: Unable to allocate storage for kernels!\n");
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error = CL_OUT_OF_HOST_MEMORY;
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goto exit;
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}
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memset(test_info.k[i], 0, array_size);
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}
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test_info.tinfo =
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(ThreadInfo *)malloc(test_info.threadCount * sizeof(*test_info.tinfo));
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if (NULL == test_info.tinfo)
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{
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vlog_error(
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"Error: Unable to allocate storage for thread specific data.\n");
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error = CL_OUT_OF_HOST_MEMORY;
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goto exit;
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}
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memset(test_info.tinfo, 0,
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test_info.threadCount * sizeof(*test_info.tinfo));
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for (i = 0; i < test_info.threadCount; i++)
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{
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cl_buffer_region region = {
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i * test_info.subBufferSize * sizeof(cl_float),
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test_info.subBufferSize * sizeof(cl_float)
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};
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test_info.tinfo[i].inBuf =
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clCreateSubBuffer(gInBuffer, CL_MEM_READ_ONLY,
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CL_BUFFER_CREATE_TYPE_REGION, ®ion, &error);
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if (error || NULL == test_info.tinfo[i].inBuf)
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{
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vlog_error("Error: Unable to create sub-buffer of gInBuffer for "
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"region {%zd, %zd}\n",
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region.origin, region.size);
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goto exit;
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}
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for (j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++)
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{
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test_info.tinfo[i].outBuf[j] = clCreateSubBuffer(
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gOutBuffer[j], CL_MEM_WRITE_ONLY, CL_BUFFER_CREATE_TYPE_REGION,
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®ion, &error);
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if (error || NULL == test_info.tinfo[i].outBuf[j])
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{
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vlog_error("Error: Unable to create sub-buffer of "
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"gOutBuffer[%d] for region {%zd, %zd}\n",
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(int)j, region.origin, region.size);
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goto exit;
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}
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}
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test_info.tinfo[i].tQueue =
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clCreateCommandQueue(gContext, gDevice, 0, &error);
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if (NULL == test_info.tinfo[i].tQueue || error)
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{
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vlog_error("clCreateCommandQueue failed. (%d)\n", error);
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goto exit;
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}
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}
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// Check for special cases for unary float
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test_info.isRangeLimited = 0;
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test_info.half_sin_cos_tan_limit = 0;
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if (0 == strcmp(f->name, "half_sin") || 0 == strcmp(f->name, "half_cos"))
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{
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test_info.isRangeLimited = 1;
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test_info.half_sin_cos_tan_limit = 1.0f
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+ test_info.ulps
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* (FLT_EPSILON / 2.0f); // out of range results from finite
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// inputs must be in [-1,1]
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}
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else if (0 == strcmp(f->name, "half_tan"))
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{
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test_info.isRangeLimited = 1;
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test_info.half_sin_cos_tan_limit =
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INFINITY; // out of range resut from finite inputs must be numeric
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}
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// Init the kernels
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{
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BuildKernelInfo build_info = {
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gMinVectorSizeIndex, test_info.threadCount, test_info.k,
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test_info.programs, f->nameInCode, relaxedMode
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};
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if ((error = ThreadPool_Do(BuildKernelFn,
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gMaxVectorSizeIndex - gMinVectorSizeIndex,
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&build_info)))
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goto exit;
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}
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// Run the kernels
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if (!gSkipCorrectnessTesting || skipTestingRelaxed)
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{
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error = ThreadPool_Do(Test, test_info.jobCount, &test_info);
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// Accumulate the arithmetic errors
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for (i = 0; i < test_info.threadCount; i++)
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{
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if (test_info.tinfo[i].maxError > maxError)
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{
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maxError = test_info.tinfo[i].maxError;
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maxErrorVal = test_info.tinfo[i].maxErrorValue;
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}
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}
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if (error) goto exit;
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if (gWimpyMode)
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vlog("Wimp pass");
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else
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vlog("passed");
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if (skipTestingRelaxed)
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{
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vlog(" (rlx skip correctness testing)\n");
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goto exit;
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}
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vlog("\t%8.2f @ %a", maxError, maxErrorVal);
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}
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vlog("\n");
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exit:
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// Release
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for (i = gMinVectorSizeIndex; i < gMaxVectorSizeIndex; i++)
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{
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clReleaseProgram(test_info.programs[i]);
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if (test_info.k[i])
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{
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for (j = 0; j < test_info.threadCount; j++)
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clReleaseKernel(test_info.k[i][j]);
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free(test_info.k[i]);
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}
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}
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if (test_info.tinfo)
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{
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for (i = 0; i < test_info.threadCount; i++)
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{
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clReleaseMemObject(test_info.tinfo[i].inBuf);
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for (j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++)
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clReleaseMemObject(test_info.tinfo[i].outBuf[j]);
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clReleaseCommandQueue(test_info.tinfo[i].tQueue);
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}
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free(test_info.tinfo);
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}
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return error;
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}
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static cl_int Test(cl_uint job_id, cl_uint thread_id, void *data)
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{
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const TestInfo *job = (const TestInfo *)data;
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size_t buffer_elements = job->subBufferSize;
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size_t buffer_size = buffer_elements * sizeof(cl_float);
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cl_uint scale = job->scale;
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cl_uint base = job_id * (cl_uint)job->step;
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ThreadInfo *tinfo = job->tinfo + thread_id;
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fptr func = job->f->func;
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const char *fname = job->f->name;
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bool relaxedMode = job->relaxedMode;
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float ulps = getAllowedUlpError(job->f, relaxedMode);
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if (relaxedMode)
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{
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func = job->f->rfunc;
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}
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cl_uint j, k;
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cl_int error;
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int isRangeLimited = job->isRangeLimited;
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float half_sin_cos_tan_limit = job->half_sin_cos_tan_limit;
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int ftz = job->ftz;
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// start the map of the output arrays
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cl_event e[VECTOR_SIZE_COUNT];
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cl_uint *out[VECTOR_SIZE_COUNT];
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for (j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++)
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{
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out[j] = (cl_uint *)clEnqueueMapBuffer(
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tinfo->tQueue, tinfo->outBuf[j], CL_FALSE, CL_MAP_WRITE, 0,
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buffer_size, 0, NULL, e + j, &error);
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if (error || NULL == out[j])
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{
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vlog_error("Error: clEnqueueMapBuffer %d failed! err: %d\n", j,
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error);
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return error;
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}
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}
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// Get that moving
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if ((error = clFlush(tinfo->tQueue))) vlog("clFlush failed\n");
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// Write the new values to the input array
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cl_uint *p = (cl_uint *)gIn + thread_id * buffer_elements;
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for (j = 0; j < buffer_elements; j++)
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{
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p[j] = base + j * scale;
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if (relaxedMode)
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{
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float p_j = *(float *)&p[j];
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if (strcmp(fname, "sin") == 0
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|| strcmp(fname, "cos")
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== 0) // the domain of the function is [-pi,pi]
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{
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if (fabs(p_j) > M_PI) ((float *)p)[j] = NAN;
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}
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if (strcmp(fname, "reciprocal") == 0)
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{
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const float l_limit = HEX_FLT(+, 1, 0, -, 126);
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const float u_limit = HEX_FLT(+, 1, 0, +, 126);
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if (fabs(p_j) < l_limit
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|| fabs(p_j) > u_limit) // the domain of the function is
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// [2^-126,2^126]
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((float *)p)[j] = NAN;
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}
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}
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}
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if ((error = clEnqueueWriteBuffer(tinfo->tQueue, tinfo->inBuf, CL_FALSE, 0,
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buffer_size, p, 0, NULL, NULL)))
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{
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vlog_error("Error: clEnqueueWriteBuffer failed! err: %d\n", error);
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return error;
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}
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for (j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++)
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{
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// Wait for the map to finish
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if ((error = clWaitForEvents(1, e + j)))
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{
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vlog_error("Error: clWaitForEvents failed! err: %d\n", error);
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return error;
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}
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if ((error = clReleaseEvent(e[j])))
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{
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vlog_error("Error: clReleaseEvent failed! err: %d\n", error);
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return error;
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}
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// Fill the result buffer with garbage, so that old results don't carry
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// over
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uint32_t pattern = 0xffffdead;
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memset_pattern4(out[j], &pattern, buffer_size);
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if ((error = clEnqueueUnmapMemObject(tinfo->tQueue, tinfo->outBuf[j],
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out[j], 0, NULL, NULL)))
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{
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vlog_error("Error: clEnqueueMapBuffer failed! err: %d\n", error);
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return error;
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}
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// run the kernel
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size_t vectorCount =
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(buffer_elements + sizeValues[j] - 1) / sizeValues[j];
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cl_kernel kernel = job->k[j][thread_id]; // each worker thread has its
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// own copy of the cl_kernel
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cl_program program = job->programs[j];
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if ((error = clSetKernelArg(kernel, 0, sizeof(tinfo->outBuf[j]),
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&tinfo->outBuf[j])))
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{
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LogBuildError(program);
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return error;
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}
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if ((error = clSetKernelArg(kernel, 1, sizeof(tinfo->inBuf),
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&tinfo->inBuf)))
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{
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LogBuildError(program);
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return error;
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}
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if ((error = clEnqueueNDRangeKernel(tinfo->tQueue, kernel, 1, NULL,
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&vectorCount, NULL, 0, NULL, NULL)))
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{
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vlog_error("FAILED -- could not execute kernel\n");
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return error;
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}
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}
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// Get that moving
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if ((error = clFlush(tinfo->tQueue))) vlog("clFlush 2 failed\n");
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if (gSkipCorrectnessTesting) return CL_SUCCESS;
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// Calculate the correctly rounded reference result
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float *r = (float *)gOut_Ref + thread_id * buffer_elements;
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float *s = (float *)p;
|
|
for (j = 0; j < buffer_elements; j++) r[j] = (float)func.f_f(s[j]);
|
|
|
|
// Read the data back -- no need to wait for the first N-1 buffers but wait
|
|
// for the last buffer. This is an in order queue.
|
|
for (j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++)
|
|
{
|
|
cl_bool blocking = (j + 1 < gMaxVectorSizeIndex) ? CL_FALSE : CL_TRUE;
|
|
out[j] = (cl_uint *)clEnqueueMapBuffer(
|
|
tinfo->tQueue, tinfo->outBuf[j], blocking, CL_MAP_READ, 0,
|
|
buffer_size, 0, NULL, NULL, &error);
|
|
if (error || NULL == out[j])
|
|
{
|
|
vlog_error("Error: clEnqueueMapBuffer %d failed! err: %d\n", j,
|
|
error);
|
|
return error;
|
|
}
|
|
}
|
|
|
|
// Verify data
|
|
uint32_t *t = (uint32_t *)r;
|
|
for (j = 0; j < buffer_elements; j++)
|
|
{
|
|
for (k = gMinVectorSizeIndex; k < gMaxVectorSizeIndex; k++)
|
|
{
|
|
uint32_t *q = out[k];
|
|
|
|
// If we aren't getting the correctly rounded result
|
|
if (t[j] != q[j])
|
|
{
|
|
float test = ((float *)q)[j];
|
|
double correct = func.f_f(s[j]);
|
|
float err = Ulp_Error(test, correct);
|
|
float abs_error = Abs_Error(test, correct);
|
|
int fail = 0;
|
|
int use_abs_error = 0;
|
|
|
|
// it is possible for the output to not match the reference
|
|
// result but for Ulp_Error to be zero, for example -1.#QNAN
|
|
// vs. 1.#QNAN. In such cases there is no failure
|
|
if (err == 0.0f)
|
|
{
|
|
fail = 0;
|
|
}
|
|
else if (relaxedMode)
|
|
{
|
|
if (strcmp(fname, "sin") == 0 || strcmp(fname, "cos") == 0)
|
|
{
|
|
fail = !(fabsf(abs_error) <= ulps);
|
|
use_abs_error = 1;
|
|
}
|
|
if (strcmp(fname, "sinpi") == 0
|
|
|| strcmp(fname, "cospi") == 0)
|
|
{
|
|
if (s[j] >= -1.0 && s[j] <= 1.0)
|
|
{
|
|
fail = !(fabsf(abs_error) <= ulps);
|
|
use_abs_error = 1;
|
|
}
|
|
}
|
|
|
|
if (strcmp(fname, "reciprocal") == 0)
|
|
{
|
|
fail = !(fabsf(err) <= ulps);
|
|
}
|
|
|
|
if (strcmp(fname, "exp") == 0 || strcmp(fname, "exp2") == 0)
|
|
{
|
|
float exp_error = ulps;
|
|
|
|
if (!gIsEmbedded)
|
|
{
|
|
exp_error += floor(fabs(2 * s[j]));
|
|
}
|
|
|
|
fail = !(fabsf(err) <= exp_error);
|
|
ulps = exp_error;
|
|
}
|
|
if (strcmp(fname, "tan") == 0)
|
|
{
|
|
|
|
if (!gFastRelaxedDerived)
|
|
{
|
|
fail = !(fabsf(err) <= ulps);
|
|
}
|
|
// Else fast math derived implementation does not
|
|
// require ULP verification
|
|
}
|
|
if (strcmp(fname, "exp10") == 0)
|
|
{
|
|
if (!gFastRelaxedDerived)
|
|
{
|
|
fail = !(fabsf(err) <= ulps);
|
|
}
|
|
// Else fast math derived implementation does not
|
|
// require ULP verification
|
|
}
|
|
if (strcmp(fname, "log") == 0 || strcmp(fname, "log2") == 0
|
|
|| strcmp(fname, "log10") == 0)
|
|
{
|
|
if (s[j] >= 0.5 && s[j] <= 2)
|
|
{
|
|
fail = !(fabsf(abs_error) <= ulps);
|
|
}
|
|
else
|
|
{
|
|
ulps = gIsEmbedded ? job->f->float_embedded_ulps
|
|
: job->f->float_ulps;
|
|
fail = !(fabsf(err) <= ulps);
|
|
}
|
|
}
|
|
|
|
|
|
// fast-relaxed implies finite-only
|
|
if (IsFloatInfinity(correct) || IsFloatNaN(correct)
|
|
|| IsFloatInfinity(s[j]) || IsFloatNaN(s[j]))
|
|
{
|
|
fail = 0;
|
|
err = 0;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
fail = !(fabsf(err) <= ulps);
|
|
}
|
|
|
|
// half_sin/cos/tan are only valid between +-2**16, Inf, NaN
|
|
if (isRangeLimited
|
|
&& fabsf(s[j]) > MAKE_HEX_FLOAT(0x1.0p16f, 0x1L, 16)
|
|
&& fabsf(s[j]) < INFINITY)
|
|
{
|
|
if (fabsf(test) <= half_sin_cos_tan_limit)
|
|
{
|
|
err = 0;
|
|
fail = 0;
|
|
}
|
|
}
|
|
|
|
if (fail)
|
|
{
|
|
if (ftz)
|
|
{
|
|
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)
|
|
{
|
|
isFloatResultSubnormalPtr =
|
|
&IsFloatResultSubnormalAbsError;
|
|
}
|
|
else
|
|
{
|
|
isFloatResultSubnormalPtr = &IsFloatResultSubnormal;
|
|
}
|
|
// retry per section 6.5.3.2
|
|
if ((*isFloatResultSubnormalPtr)(correct, ulps))
|
|
{
|
|
fail = fail && (test != 0.0f);
|
|
if (!fail) err = 0.0f;
|
|
}
|
|
|
|
// retry per section 6.5.3.3
|
|
if (IsFloatSubnormal(s[j]))
|
|
{
|
|
double correct2 = func.f_f(0.0);
|
|
double correct3 = func.f_f(-0.0);
|
|
float err2;
|
|
float err3;
|
|
if (use_abs_error)
|
|
{
|
|
err2 = Abs_Error(test, correct2);
|
|
err3 = Abs_Error(test, correct3);
|
|
}
|
|
else
|
|
{
|
|
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 ((*isFloatResultSubnormalPtr)(correct2, ulps)
|
|
|| (*isFloatResultSubnormalPtr)(correct3, ulps))
|
|
{
|
|
fail = fail && (test != 0.0f);
|
|
if (!fail) err = 0.0f;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
if (fabsf(err) > tinfo->maxError)
|
|
{
|
|
tinfo->maxError = fabsf(err);
|
|
tinfo->maxErrorValue = s[j];
|
|
}
|
|
if (fail)
|
|
{
|
|
vlog_error("\nERROR: %s%s: %f ulp error at %a (0x%8.8x): "
|
|
"*%a vs. %a\n",
|
|
job->f->name, sizeNames[k], err, ((float *)s)[j],
|
|
((uint32_t *)s)[j], ((float *)t)[j], test);
|
|
return -1;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
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:%10u buf_elements:%10zd ulps:%5.3f "
|
|
"ThreadCount:%2u\n",
|
|
base, job->step, job->scale, buffer_elements, job->ulps,
|
|
job->threadCount);
|
|
}
|
|
else
|
|
{
|
|
vlog(".");
|
|
}
|
|
fflush(stdout);
|
|
}
|
|
|
|
return CL_SUCCESS;
|
|
}
|