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https://github.com/KhronosGroup/OpenCL-CTS.git
synced 2026-03-19 14:09:03 +00:00
* The global variable `gTestFastRelaxed` has state which is used to control the behaviour of the compiler flag `-cl-fast-relaxed-math` and the precision testing of relaxed, fp32 and fp64 types. This is confusing since the global variable is being set and read in different translation units, making it very difficult to reason about the logic of the brute force framework. It is particular difficult to follow since the global variables is cached and then turned off in the case of fp32 and f64 in order to use the same code path as relaxed testing, after it is then turned back on. * Remove uses of the global variable outside of `main.cpp` (the global variable remains in use within `main.cpp` since it is a command line option and used to turn of relaxed testing completely). Replace all uses of the global variable with boolean `relaxedMode` which is passed as a function paramter but replaces `gTestFastRelaxed` semantically.
635 lines
24 KiB
C++
635 lines
24 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 "Utility.h"
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#include <string.h>
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#include "FunctionList.h"
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int TestFunc_Int_Float(const Func *f, MTdata, bool relaxedMode);
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int TestFunc_Int_Double(const Func *f, MTdata, bool relaxedMode);
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extern const vtbl _i_unary = { "i_unary", TestFunc_Int_Float,
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TestFunc_Int_Double };
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static int BuildKernel(const char *name, int vectorSize, cl_kernel *k,
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cl_program *p, bool relaxedMode);
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static int BuildKernelDouble(const char *name, int vectorSize, cl_kernel *k,
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cl_program *p, bool relaxedMode);
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static int BuildKernel(const char *name, int vectorSize, cl_kernel *k,
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cl_program *p, bool relaxedMode)
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{
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const char *c[] = { "__kernel void math_kernel", sizeNames[vectorSize], "( __global int", sizeNames[vectorSize], "* out, __global float", sizeNames[vectorSize], "* in)\n"
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"{\n"
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" int i = get_global_id(0);\n"
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" out[i] = ", name, "( in[i] );\n"
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"}\n"
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};
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const char *c3[] = { "__kernel void math_kernel", sizeNames[vectorSize], "( __global int* 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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" int3 i0 = ", name, "( f0 );\n"
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" vstore3( i0, 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 left over after BUFFER_SIZE % (3*sizeof(float)). Assume power of two 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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" int3 i0 = ", name, "( 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] = i0.y; \n"
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" // fall through\n"
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" case 1:\n"
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" out[3*i] = i0.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", sizeNames[vectorSize] );
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return MakeKernel(kern, (cl_uint)kernSize, testName, k, p, relaxedMode);
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}
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static int BuildKernelDouble(const char *name, int vectorSize, cl_kernel *k,
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cl_program *p, bool relaxedMode)
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{
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const char *c[] = { "#pragma OPENCL EXTENSION cl_khr_fp64 : enable\n",
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"__kernel void math_kernel", sizeNames[vectorSize], "( __global int", sizeNames[vectorSize], "* out, __global double", sizeNames[vectorSize], "* in)\n"
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"{\n"
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" int i = get_global_id(0);\n"
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" out[i] = ", name, "( in[i] );\n"
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"}\n"
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};
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const char *c3[] = {"#pragma OPENCL EXTENSION cl_khr_fp64 : enable\n",
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"__kernel void math_kernel", sizeNames[vectorSize], "( __global int* out, __global double* 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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" double3 f0 = vload3( 0, in + 3 * i );\n"
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" int3 i0 = ", name, "( f0 );\n"
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" vstore3( i0, 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 left over after BUFFER_SIZE % (3*sizeof(float)). Assume power of two buffer size \n"
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" double3 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 = (double3)( in[3*i], NAN, NAN ); \n"
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" break;\n"
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" case 0:\n"
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" f0 = (double3)( in[3*i], in[3*i+1], NAN ); \n"
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" break;\n"
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" }\n"
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" int3 i0 = ", name, "( 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] = i0.y; \n"
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" // fall through\n"
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" case 1:\n"
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" out[3*i] = i0.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", sizeNames[vectorSize] );
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return MakeKernel(kern, (cl_uint)kernSize, testName, k, p, 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_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 BuildKernel_FloatFn( cl_uint job_id, cl_uint thread_id UNUSED, void *p );
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static cl_int BuildKernel_FloatFn( 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->kernels + i,
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info->programs + i, info->relaxedMode);
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}
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static cl_int BuildKernel_DoubleFn( cl_uint job_id, cl_uint thread_id UNUSED, void *p );
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static cl_int BuildKernel_DoubleFn( 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 BuildKernelDouble(info->nameInCode, i, info->kernels + i,
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info->programs + i, info->relaxedMode);
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}
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int TestFunc_Int_Float(const Func *f, MTdata d, bool relaxedMode)
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{
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uint64_t i;
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uint32_t j, k;
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int error;
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cl_program programs[ VECTOR_SIZE_COUNT ];
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cl_kernel kernels[ VECTOR_SIZE_COUNT ];
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int ftz = f->ftz || 0 == (gFloatCapabilities & CL_FP_DENORM) || gForceFTZ;
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size_t bufferSize = (gWimpyMode)?gWimpyBufferSize:BUFFER_SIZE;
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uint64_t step = bufferSize / sizeof( float );
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int scale = (int)((1ULL<<32) / (16 * bufferSize / sizeof( float )) + 1);
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logFunctionInfo(f->name, sizeof(cl_float), relaxedMode);
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if( gWimpyMode )
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{
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step = (1ULL<<32) * gWimpyReductionFactor / (512);
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}
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// This test is not using ThreadPool so we need to disable FTZ here
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// for reference computations
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FPU_mode_type oldMode;
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DisableFTZ(&oldMode);
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Force64BitFPUPrecision();
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// Init the kernels
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BuildKernelInfo build_info = { gMinVectorSizeIndex, kernels, programs,
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f->nameInCode, relaxedMode };
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if( (error = ThreadPool_Do( BuildKernel_FloatFn, gMaxVectorSizeIndex - gMinVectorSizeIndex, &build_info ) ))
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return error;
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/*
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for( i = gMinVectorSizeIndex; i < gMaxVectorSizeIndex; i++ )
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if( (error = BuildKernel( f->nameInCode, (int) i, kernels + i, programs + i) ) )
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return error;
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*/
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for( i = 0; i < (1ULL<<32); i += step )
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{
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//Init input array
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uint32_t *p = (uint32_t *)gIn;
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if( gWimpyMode )
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{
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for( j = 0; j < bufferSize / sizeof( float ); j++ )
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p[j] = (uint32_t) i + j * scale;
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}
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else
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{
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for( j = 0; j < bufferSize / sizeof( float ); j++ )
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p[j] = (uint32_t) i + j;
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}
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if( (error = clEnqueueWriteBuffer(gQueue, gInBuffer, CL_FALSE, 0, bufferSize, gIn, 0, NULL, NULL) ))
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{
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vlog_error( "\n*** Error %d in clEnqueueWriteBuffer ***\n", error );
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return error;
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}
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// write garbage into output arrays
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for( j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++ )
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{
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uint32_t pattern = 0xffffdead;
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memset_pattern4(gOut[j], &pattern, bufferSize);
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if( (error = clEnqueueWriteBuffer(gQueue, gOutBuffer[j], CL_FALSE, 0, bufferSize, gOut[j], 0, NULL, NULL) ))
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{
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vlog_error( "\n*** Error %d in clEnqueueWriteBuffer2(%d) ***\n", error, j );
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goto exit;
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}
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}
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// Run the kernels
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for( j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++ )
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{
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size_t vectorSize = sizeValues[j] * sizeof(cl_float);
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size_t localCount = (bufferSize + vectorSize - 1) / vectorSize;
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if( ( error = clSetKernelArg(kernels[j], 0, sizeof( gOutBuffer[j] ), &gOutBuffer[j] ) )) { LogBuildError(programs[j]); goto exit; }
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if( ( error = clSetKernelArg( kernels[j], 1, sizeof( gInBuffer ), &gInBuffer ) )) { LogBuildError(programs[j]); goto exit; }
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if( (error = clEnqueueNDRangeKernel(gQueue, kernels[j], 1, NULL, &localCount, NULL, 0, NULL, NULL)) )
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{
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vlog_error( "FAILED -- could not execute kernel\n" );
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goto exit;
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}
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}
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// Get that moving
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if( (error = clFlush(gQueue) ))
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vlog( "clFlush failed\n" );
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//Calculate the correctly rounded reference result
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int *r = (int *)gOut_Ref;
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float *s = (float *)gIn;
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for( j = 0; j < bufferSize / sizeof( float ); j++ )
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r[j] = f->func.i_f( s[j] );
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// Read the data back
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for( j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++ )
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{
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if( (error = clEnqueueReadBuffer(gQueue, gOutBuffer[j], CL_TRUE, 0, bufferSize, gOut[j], 0, NULL, NULL)) )
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{
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vlog_error( "ReadArray failed %d\n", error );
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goto exit;
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}
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}
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if( gSkipCorrectnessTesting )
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break;
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//Verify data
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uint32_t *t = (uint32_t *)gOut_Ref;
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for( j = 0; j < bufferSize / sizeof( float ); j++ )
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{
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for( k = gMinVectorSizeIndex; k < gMaxVectorSizeIndex; k++ )
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{
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uint32_t *q = (uint32_t *)(gOut[k]);
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// If we aren't getting the correctly rounded result
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if( t[j] != q[j] )
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{
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if( ftz && IsFloatSubnormal(s[j]))
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{
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unsigned int correct0 = f->func.i_f( 0.0 );
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unsigned int correct1 = f->func.i_f( -0.0 );
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if( q[j] == correct0 || q[j] == correct1 )
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continue;
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}
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uint32_t err = t[j] - q[j];
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if( q[j] > t[j] )
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err = q[j] - t[j];
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vlog_error( "\nERROR: %s%s: %d ulp error at %a (0x%8.8x): *%d vs. %d\n", f->name, sizeNames[k], err, ((float*) gIn)[j], ((cl_uint*) gIn)[j], t[j], q[j] );
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error = -1;
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goto exit;
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}
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}
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}
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if( 0 == (i & 0x0fffffff) )
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{
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if (gVerboseBruteForce)
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{
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vlog("base:%14u step:%10zu bufferSize:%10zd \n", i, step, bufferSize);
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} else
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{
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vlog("." );
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}
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fflush(stdout);
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}
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}
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if( ! gSkipCorrectnessTesting )
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{
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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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}
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if( gMeasureTimes )
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{
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//Init input array
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uint32_t *p = (uint32_t *)gIn;
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for( j = 0; j < bufferSize / sizeof( float ); j++ )
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p[j] = genrand_int32(d);
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if( (error = clEnqueueWriteBuffer(gQueue, gInBuffer, CL_FALSE, 0, bufferSize, gIn, 0, NULL, NULL) ))
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{
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vlog_error( "\n*** Error %d in clEnqueueWriteBuffer ***\n", error );
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return error;
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}
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// Run the kernels
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for( j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++ )
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{
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size_t vectorSize = sizeValues[j] * sizeof(cl_float);
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size_t localCount = (bufferSize + vectorSize - 1) / vectorSize;
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if( ( error = clSetKernelArg(kernels[j], 0, sizeof( gOutBuffer[j] ), &gOutBuffer[j] ) )) { LogBuildError(programs[j]); goto exit; }
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if( ( error = clSetKernelArg( kernels[j], 1, sizeof( gInBuffer ), &gInBuffer ) )) { LogBuildError(programs[j]); goto exit; }
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double sum = 0.0;
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double bestTime = INFINITY;
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for( k = 0; k < PERF_LOOP_COUNT; k++ )
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{
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uint64_t startTime = GetTime();
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if( (error = clEnqueueNDRangeKernel(gQueue, kernels[j], 1, NULL, &localCount, NULL, 0, NULL, NULL)) )
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{
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vlog_error( "FAILED -- could not execute kernel\n" );
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goto exit;
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}
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// Make sure OpenCL is done
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if( (error = clFinish(gQueue) ) )
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{
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vlog_error( "Error %d at clFinish\n", error );
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goto exit;
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}
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uint64_t endTime = GetTime();
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double time = SubtractTime( endTime, startTime );
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sum += time;
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if( time < bestTime )
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bestTime = time;
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}
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if( gReportAverageTimes )
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bestTime = sum / PERF_LOOP_COUNT;
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double clocksPerOp = bestTime * (double) gDeviceFrequency * gComputeDevices * gSimdSize * 1e6 / (bufferSize / sizeof( float ) );
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vlog_perf( clocksPerOp, LOWER_IS_BETTER, "clocks / element", "%sf%s", f->name, sizeNames[j] );
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}
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}
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vlog( "\n" );
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exit:
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RestoreFPState(&oldMode);
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// Release
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for( k = gMinVectorSizeIndex; k < gMaxVectorSizeIndex; k++ )
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{
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clReleaseKernel(kernels[k]);
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clReleaseProgram(programs[k]);
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}
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return error;
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}
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int TestFunc_Int_Double(const Func *f, MTdata d, bool relaxedMode)
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{
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uint64_t i;
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uint32_t j, k;
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int error;
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cl_program programs[ VECTOR_SIZE_COUNT ];
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cl_kernel kernels[ VECTOR_SIZE_COUNT ];
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int ftz = f->ftz || gForceFTZ;
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size_t bufferSize = (gWimpyMode)?gWimpyBufferSize:BUFFER_SIZE;
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uint64_t step = bufferSize / sizeof( cl_double );
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int scale = (int)((1ULL<<32) / (16 * bufferSize / sizeof( cl_double )) + 1);
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logFunctionInfo(f->name, sizeof(cl_double), relaxedMode);
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if( gWimpyMode )
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{
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step = (1ULL<<32) * gWimpyReductionFactor / (512);
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}
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// This test is not using ThreadPool so we need to disable FTZ here
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// for reference computations
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FPU_mode_type oldMode;
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DisableFTZ(&oldMode);
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Force64BitFPUPrecision();
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// Init the kernels
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BuildKernelInfo build_info = { gMinVectorSizeIndex, kernels, programs,
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f->nameInCode, relaxedMode };
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if( (error = ThreadPool_Do( BuildKernel_DoubleFn,
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gMaxVectorSizeIndex - gMinVectorSizeIndex,
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&build_info ) ))
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{
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return error;
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}
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/*
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for( i = gMinVectorSizeIndex; i < gMaxVectorSizeIndex; i++ )
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if( (error = BuildKernelDouble( f->nameInCode, (int) i, kernels + i, programs + i) ) )
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return error;
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*/
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for( i = 0; i < (1ULL<<32); i += step )
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{
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//Init input array
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double *p = (double *)gIn;
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if( gWimpyMode )
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{
|
|
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;
|
|
}
|
|
}
|
|
|
|
// 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( 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
|
|
int *r = (int *)gOut_Ref;
|
|
double *s = (double *)gIn;
|
|
for( j = 0; j < bufferSize / sizeof( cl_double ); j++ )
|
|
r[j] = f->dfunc.i_f( s[j] );
|
|
|
|
// 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( gSkipCorrectnessTesting )
|
|
break;
|
|
|
|
//Verify data
|
|
uint32_t *t = (uint32_t *)gOut_Ref;
|
|
for( j = 0; j < bufferSize / sizeof( cl_double ); j++ )
|
|
{
|
|
for( k = gMinVectorSizeIndex; k < gMaxVectorSizeIndex; k++ )
|
|
{
|
|
uint32_t *q = (uint32_t *)(gOut[k]);
|
|
// If we aren't getting the correctly rounded result
|
|
if( t[j] != q[j] )
|
|
{
|
|
if( ftz && IsDoubleSubnormal(s[j]))
|
|
{
|
|
unsigned int correct0 = f->dfunc.i_f( 0.0 );
|
|
unsigned int correct1 = f->dfunc.i_f( -0.0 );
|
|
if( q[j] == correct0 || q[j] == correct1 )
|
|
continue;
|
|
}
|
|
|
|
uint32_t err = t[j] - q[j];
|
|
if( q[j] > t[j] )
|
|
err = q[j] - t[j];
|
|
vlog_error( "\nERROR: %sD%s: %d ulp error at %.13la: *%d vs. %d\n", f->name, sizeNames[k], err, ((double*) gIn)[j], t[j], q[j] );
|
|
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( cl_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( 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 -- " );
|
|
}
|
|
|
|
vlog( "\n" );
|
|
|
|
|
|
exit:
|
|
RestoreFPState(&oldMode);
|
|
// Release
|
|
for( k = gMinVectorSizeIndex; k < gMaxVectorSizeIndex; k++ )
|
|
{
|
|
clReleaseKernel(kernels[k]);
|
|
clReleaseProgram(programs[k]);
|
|
}
|
|
|
|
return error;
|
|
}
|
|
|