mirror of
https://github.com/KhronosGroup/OpenCL-CTS.git
synced 2026-03-19 14:09:03 +00:00
Add a type argument so that in the future we can request the ULP requirement for fp16 and fp64 types through `getAllowedUlpError` too. Contributes to https://github.com/KhronosGroup/OpenCL-CTS/issues/867 Signed-off-by: Sven van Haastregt <sven.vanhaastregt@arm.com>
871 lines
34 KiB
C++
871 lines
34 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 "common.h"
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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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namespace {
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const float twoToMinus126 = MAKE_HEX_FLOAT(0x1p-126f, 1, -126);
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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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auto generator = [](const std::string &kernel_name, const char *builtin,
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cl_uint vector_size_index) {
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return GetBinaryKernel(kernel_name, builtin, ParameterType::Float,
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ParameterType::Float, ParameterType::Float,
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vector_size_index);
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};
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return BuildKernels(info, job_id, generator);
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}
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// Thread specific data for a worker thread
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struct ThreadInfo
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{
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// Input and output buffers for the thread
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clMemWrapper inBuf;
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clMemWrapper inBuf2;
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Buffers outBuf;
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float maxError; // max error value. Init to 0.
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double
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maxErrorValue; // position of the max error value (param 1). Init to 0.
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double maxErrorValue2; // position of the max error value (param 2). Init
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// to 0.
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MTdataHolder d;
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// Per thread command queue to improve performance
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clCommandQueueWrapper tQueue;
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};
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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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// Programs for various vector sizes.
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Programs programs;
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// Thread-specific kernels for each vector size:
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// k[vector_size][thread_id]
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KernelMatrix k;
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// Array of thread specific information
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std::vector<ThreadInfo> tinfo;
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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 isFDim;
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int skipNanInf;
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int isNextafter;
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bool relaxedMode; // True if test is running in relaxed mode, false
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// otherwise.
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};
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// A table of more difficult cases to get right
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const float specialValues[] = {
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-NAN,
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-INFINITY,
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-FLT_MAX,
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MAKE_HEX_FLOAT(-0x1.000002p64f, -0x1000002L, 40),
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MAKE_HEX_FLOAT(-0x1.0p64f, -0x1L, 64),
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MAKE_HEX_FLOAT(-0x1.fffffep63f, -0x1fffffeL, 39),
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MAKE_HEX_FLOAT(-0x1.000002p63f, -0x1000002L, 39),
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MAKE_HEX_FLOAT(-0x1.0p63f, -0x1L, 63),
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MAKE_HEX_FLOAT(-0x1.fffffep62f, -0x1fffffeL, 38),
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MAKE_HEX_FLOAT(-0x1.000002p32f, -0x1000002L, 8),
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MAKE_HEX_FLOAT(-0x1.0p32f, -0x1L, 32),
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MAKE_HEX_FLOAT(-0x1.fffffep31f, -0x1fffffeL, 7),
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MAKE_HEX_FLOAT(-0x1.000002p31f, -0x1000002L, 7),
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MAKE_HEX_FLOAT(-0x1.0p31f, -0x1L, 31),
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MAKE_HEX_FLOAT(-0x1.fffffep30f, -0x1fffffeL, 6),
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-1000.f,
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-100.f,
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-4.0f,
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-3.5f,
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-3.0f,
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MAKE_HEX_FLOAT(-0x1.800002p1f, -0x1800002L, -23),
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-2.5f,
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MAKE_HEX_FLOAT(-0x1.7ffffep1f, -0x17ffffeL, -23),
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-2.0f,
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MAKE_HEX_FLOAT(-0x1.800002p0f, -0x1800002L, -24),
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-1.5f,
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MAKE_HEX_FLOAT(-0x1.7ffffep0f, -0x17ffffeL, -24),
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MAKE_HEX_FLOAT(-0x1.000002p0f, -0x1000002L, -24),
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-1.0f,
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MAKE_HEX_FLOAT(-0x1.fffffep-1f, -0x1fffffeL, -25),
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MAKE_HEX_FLOAT(-0x1.000002p-1f, -0x1000002L, -25),
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-0.5f,
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MAKE_HEX_FLOAT(-0x1.fffffep-2f, -0x1fffffeL, -26),
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MAKE_HEX_FLOAT(-0x1.000002p-2f, -0x1000002L, -26),
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-0.25f,
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MAKE_HEX_FLOAT(-0x1.fffffep-3f, -0x1fffffeL, -27),
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MAKE_HEX_FLOAT(-0x1.000002p-126f, -0x1000002L, -150),
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-FLT_MIN,
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MAKE_HEX_FLOAT(-0x0.fffffep-126f, -0x0fffffeL, -150),
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MAKE_HEX_FLOAT(-0x0.000ffep-126f, -0x0000ffeL, -150),
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MAKE_HEX_FLOAT(-0x0.0000fep-126f, -0x00000feL, -150),
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MAKE_HEX_FLOAT(-0x0.00000ep-126f, -0x000000eL, -150),
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MAKE_HEX_FLOAT(-0x0.00000cp-126f, -0x000000cL, -150),
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MAKE_HEX_FLOAT(-0x0.00000ap-126f, -0x000000aL, -150),
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MAKE_HEX_FLOAT(-0x0.000008p-126f, -0x0000008L, -150),
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MAKE_HEX_FLOAT(-0x0.000006p-126f, -0x0000006L, -150),
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MAKE_HEX_FLOAT(-0x0.000004p-126f, -0x0000004L, -150),
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MAKE_HEX_FLOAT(-0x0.000002p-126f, -0x0000002L, -150),
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-0.0f,
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+NAN,
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+INFINITY,
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+FLT_MAX,
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MAKE_HEX_FLOAT(+0x1.000002p64f, +0x1000002L, 40),
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MAKE_HEX_FLOAT(+0x1.0p64f, +0x1L, 64),
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MAKE_HEX_FLOAT(+0x1.fffffep63f, +0x1fffffeL, 39),
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MAKE_HEX_FLOAT(+0x1.000002p63f, +0x1000002L, 39),
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MAKE_HEX_FLOAT(+0x1.0p63f, +0x1L, 63),
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MAKE_HEX_FLOAT(+0x1.fffffep62f, +0x1fffffeL, 38),
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MAKE_HEX_FLOAT(+0x1.000002p32f, +0x1000002L, 8),
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MAKE_HEX_FLOAT(+0x1.0p32f, +0x1L, 32),
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MAKE_HEX_FLOAT(+0x1.fffffep31f, +0x1fffffeL, 7),
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MAKE_HEX_FLOAT(+0x1.000002p31f, +0x1000002L, 7),
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MAKE_HEX_FLOAT(+0x1.0p31f, +0x1L, 31),
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MAKE_HEX_FLOAT(+0x1.fffffep30f, +0x1fffffeL, 6),
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+1000.f,
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+100.f,
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+4.0f,
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+3.5f,
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+3.0f,
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MAKE_HEX_FLOAT(+0x1.800002p1f, +0x1800002L, -23),
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2.5f,
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MAKE_HEX_FLOAT(+0x1.7ffffep1f, +0x17ffffeL, -23),
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+2.0f,
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MAKE_HEX_FLOAT(+0x1.800002p0f, +0x1800002L, -24),
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1.5f,
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MAKE_HEX_FLOAT(+0x1.7ffffep0f, +0x17ffffeL, -24),
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MAKE_HEX_FLOAT(+0x1.000002p0f, +0x1000002L, -24),
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+1.0f,
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MAKE_HEX_FLOAT(+0x1.fffffep-1f, +0x1fffffeL, -25),
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MAKE_HEX_FLOAT(+0x1.000002p-1f, +0x1000002L, -25),
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+0.5f,
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MAKE_HEX_FLOAT(+0x1.fffffep-2f, +0x1fffffeL, -26),
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MAKE_HEX_FLOAT(+0x1.000002p-2f, +0x1000002L, -26),
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+0.25f,
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MAKE_HEX_FLOAT(+0x1.fffffep-3f, +0x1fffffeL, -27),
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MAKE_HEX_FLOAT(0x1.000002p-126f, 0x1000002L, -150),
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+FLT_MIN,
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MAKE_HEX_FLOAT(+0x0.fffffep-126f, +0x0fffffeL, -150),
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MAKE_HEX_FLOAT(+0x0.000ffep-126f, +0x0000ffeL, -150),
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MAKE_HEX_FLOAT(+0x0.0000fep-126f, +0x00000feL, -150),
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MAKE_HEX_FLOAT(+0x0.00000ep-126f, +0x000000eL, -150),
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MAKE_HEX_FLOAT(+0x0.00000cp-126f, +0x000000cL, -150),
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MAKE_HEX_FLOAT(+0x0.00000ap-126f, +0x000000aL, -150),
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MAKE_HEX_FLOAT(+0x0.000008p-126f, +0x0000008L, -150),
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MAKE_HEX_FLOAT(+0x0.000006p-126f, +0x0000006L, -150),
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MAKE_HEX_FLOAT(+0x0.000004p-126f, +0x0000004L, -150),
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MAKE_HEX_FLOAT(+0x0.000002p-126f, +0x0000002L, -150),
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+0.0f,
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};
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constexpr size_t specialValuesCount =
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sizeof(specialValues) / sizeof(specialValues[0]);
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cl_int Test(cl_uint job_id, cl_uint thread_id, void *data)
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{
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TestInfo *job = (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 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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int ftz = job->ftz;
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bool relaxedMode = job->relaxedMode;
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float ulps = getAllowedUlpError(job->f, kfloat, relaxedMode);
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MTdata d = tinfo->d;
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cl_int error;
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std::vector<bool> overflow(buffer_elements, false);
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const char *name = job->f->name;
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int isFDim = job->isFDim;
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int skipNanInf = job->skipNanInf;
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int isNextafter = job->isNextafter;
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cl_uint *t = 0;
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cl_float *r = 0;
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cl_float *s = 0;
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cl_float *s2 = 0;
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cl_int copysign_test = 0;
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RoundingMode oldRoundMode;
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int skipVerification = 0;
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if (relaxedMode)
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{
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func = job->f->rfunc;
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if (strcmp(name, "pow") == 0 && gFastRelaxedDerived)
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{
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ulps = INFINITY;
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skipVerification = 1;
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}
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}
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cl_event e[VECTOR_SIZE_COUNT];
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cl_uint *out[VECTOR_SIZE_COUNT];
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if (gHostFill)
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{
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// start the map of the output arrays
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for (auto 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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}
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// Init input array
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cl_uint *p = (cl_uint *)gIn + thread_id * buffer_elements;
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cl_uint *p2 = (cl_uint *)gIn2 + thread_id * buffer_elements;
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cl_uint idx = 0;
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int totalSpecialValueCount = specialValuesCount * specialValuesCount;
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int lastSpecialJobIndex = (totalSpecialValueCount - 1) / buffer_elements;
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// Test edge cases
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if (job_id <= (cl_uint)lastSpecialJobIndex)
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{
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float *fp = (float *)p;
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float *fp2 = (float *)p2;
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uint32_t x, y;
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x = (job_id * buffer_elements) % specialValuesCount;
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y = (job_id * buffer_elements) / specialValuesCount;
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for (; idx < buffer_elements; idx++)
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{
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fp[idx] = specialValues[x];
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fp2[idx] = specialValues[y];
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++x;
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if (x >= specialValuesCount)
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{
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x = 0;
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y++;
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if (y >= specialValuesCount) break;
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}
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}
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}
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// Init any remaining values
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for (; idx < buffer_elements; idx++)
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{
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p[idx] = genrand_int32(d);
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p2[idx] = genrand_int32(d);
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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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if ((error = clEnqueueWriteBuffer(tinfo->tQueue, tinfo->inBuf2, CL_FALSE, 0,
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buffer_size, p2, 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 (auto j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++)
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{
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if (gHostFill)
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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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}
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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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if (gHostFill)
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{
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memset_pattern4(out[j], &pattern, buffer_size);
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if ((error = clEnqueueUnmapMemObject(
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tinfo->tQueue, tinfo->outBuf[j], out[j], 0, NULL, NULL)))
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{
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vlog_error("Error: clEnqueueUnmapMemObject failed! err: %d\n",
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error);
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return error;
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}
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}
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else
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{
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if ((error = clEnqueueFillBuffer(tinfo->tQueue, tinfo->outBuf[j],
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&pattern, sizeof(pattern), 0,
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buffer_size, 0, NULL, NULL)))
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{
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vlog_error("Error: clEnqueueFillBuffer failed! err: %d\n",
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error);
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return error;
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}
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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 = clSetKernelArg(kernel, 2, sizeof(tinfo->inBuf2),
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&tinfo->inBuf2)))
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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)
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{
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if ((error = clFinish(tinfo->tQueue)))
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{
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vlog_error("Error: clFinish failed! err: %d\n", error);
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return error;
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}
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return CL_SUCCESS;
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}
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FPU_mode_type oldMode;
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oldRoundMode = kRoundToNearestEven;
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if (isFDim)
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{
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// Calculate the correctly rounded reference result
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memset(&oldMode, 0, sizeof(oldMode));
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if (ftz || relaxedMode) ForceFTZ(&oldMode);
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// Set the rounding mode to match the device
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if (gIsInRTZMode) oldRoundMode = set_round(kRoundTowardZero, kfloat);
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}
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if (!strcmp(name, "copysign")) copysign_test = 1;
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#define ref_func(s, s2) (copysign_test ? func.f_ff_f(s, s2) : func.f_ff(s, s2))
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// Calculate the correctly rounded reference result
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r = (float *)gOut_Ref + thread_id * buffer_elements;
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s = (float *)gIn + thread_id * buffer_elements;
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s2 = (float *)gIn2 + thread_id * buffer_elements;
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if (skipNanInf)
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{
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for (size_t j = 0; j < buffer_elements; j++)
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{
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feclearexcept(FE_OVERFLOW);
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r[j] = (float)ref_func(s[j], s2[j]);
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overflow[j] =
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FE_OVERFLOW == (FE_OVERFLOW & fetestexcept(FE_OVERFLOW));
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}
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}
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else
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{
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for (size_t j = 0; j < buffer_elements; j++)
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r[j] = (float)ref_func(s[j], s2[j]);
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}
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if (isFDim && ftz) RestoreFPState(&oldMode);
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// Read the data back -- no need to wait for the first N-1 buffers but wait
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// for the last buffer. This is an in order queue.
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for (auto 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;
|
|
}
|
|
}
|
|
|
|
if (!skipVerification)
|
|
{
|
|
// Verify data
|
|
t = (cl_uint *)r;
|
|
for (size_t j = 0; j < buffer_elements; j++)
|
|
{
|
|
for (auto k = gMinVectorSizeIndex; k < gMaxVectorSizeIndex; k++)
|
|
{
|
|
cl_uint *q = out[k];
|
|
|
|
// If we aren't getting the correctly rounded result
|
|
if (t[j] != q[j])
|
|
{
|
|
float test = ((float *)q)[j];
|
|
double correct = ref_func(s[j], s2[j]);
|
|
|
|
// Per section 10 paragraph 6, accept any result if an input
|
|
// or output is a infinity or NaN or overflow As per
|
|
// OpenCL 2.0 spec, section 5.8.4.3, enabling
|
|
// fast-relaxed-math mode also enables -cl-finite-math-only
|
|
// optimization. This optimization allows to assume that
|
|
// arguments and results are not NaNs or +/-INFs. Hence,
|
|
// accept any result if inputs or results are NaNs or INFs.
|
|
if (relaxedMode || skipNanInf)
|
|
{
|
|
if (skipNanInf && overflow[j]) continue;
|
|
// Note: no double rounding here. Reference functions
|
|
// calculate in single precision.
|
|
if (IsFloatInfinity(correct) || IsFloatNaN(correct)
|
|
|| IsFloatInfinity(s2[j]) || IsFloatNaN(s2[j])
|
|
|| IsFloatInfinity(s[j]) || IsFloatNaN(s[j]))
|
|
continue;
|
|
}
|
|
|
|
float err = Ulp_Error(test, correct);
|
|
int fail = !(fabsf(err) <= ulps);
|
|
|
|
if (fail && (ftz || relaxedMode))
|
|
{
|
|
// retry per section 6.5.3.2
|
|
if (IsFloatResultSubnormal(correct, ulps))
|
|
{
|
|
fail = fail && (test != 0.0f);
|
|
if (!fail) err = 0.0f;
|
|
}
|
|
|
|
// nextafter on FTZ platforms may return the smallest
|
|
// normal float (2^-126) given a denormal or a zero
|
|
// as the first argument. The rationale here is that
|
|
// nextafter flushes the argument to zero and then
|
|
// returns the next representable number in the
|
|
// direction of the second argument, and since
|
|
// denorms are considered as zero, the smallest
|
|
// normal number is the next representable number.
|
|
// In which case, it should have the same sign as the
|
|
// second argument.
|
|
if (isNextafter)
|
|
{
|
|
if (IsFloatSubnormal(s[j]) || s[j] == 0.0f)
|
|
{
|
|
float value = copysignf(twoToMinus126, s2[j]);
|
|
fail = fail && (test != value);
|
|
if (!fail) err = 0.0f;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
// retry per section 6.5.3.3
|
|
if (IsFloatSubnormal(s[j]))
|
|
{
|
|
double correct2, correct3;
|
|
float err2, err3;
|
|
|
|
if (skipNanInf) feclearexcept(FE_OVERFLOW);
|
|
|
|
correct2 = ref_func(0.0, s2[j]);
|
|
correct3 = ref_func(-0.0, s2[j]);
|
|
|
|
// Per section 10 paragraph 6, accept any result
|
|
// if an input or output is a infinity or NaN or
|
|
// overflow As per OpenCL 2.0 spec,
|
|
// section 5.8.4.3, enabling fast-relaxed-math
|
|
// mode also enables -cl-finite-math-only
|
|
// optimization. This optimization allows to
|
|
// assume that arguments and results are not
|
|
// NaNs or +/-INFs. Hence, accept any result if
|
|
// inputs or results are NaNs or INFs.
|
|
if (relaxedMode || skipNanInf)
|
|
{
|
|
if (fetestexcept(FE_OVERFLOW) && skipNanInf)
|
|
continue;
|
|
|
|
// Note: no double rounding here. Reference
|
|
// functions calculate in single precision.
|
|
if (IsFloatInfinity(correct2)
|
|
|| IsFloatNaN(correct2)
|
|
|| IsFloatInfinity(correct3)
|
|
|| IsFloatNaN(correct3))
|
|
continue;
|
|
}
|
|
|
|
err2 = Ulp_Error(test, correct2);
|
|
err3 = Ulp_Error(test, correct3);
|
|
fail = fail
|
|
&& ((!(fabsf(err2) <= ulps))
|
|
&& (!(fabsf(err3) <= ulps)));
|
|
if (fabsf(err2) < fabsf(err)) err = err2;
|
|
if (fabsf(err3) < fabsf(err)) err = err3;
|
|
|
|
// retry per section 6.5.3.4
|
|
if (IsFloatResultSubnormal(correct2, ulps)
|
|
|| IsFloatResultSubnormal(correct3, ulps))
|
|
{
|
|
fail = fail && (test != 0.0f);
|
|
if (!fail) err = 0.0f;
|
|
}
|
|
|
|
// try with both args as zero
|
|
if (IsFloatSubnormal(s2[j]))
|
|
{
|
|
double correct4, correct5;
|
|
float err4, err5;
|
|
|
|
if (skipNanInf) feclearexcept(FE_OVERFLOW);
|
|
|
|
correct2 = ref_func(0.0, 0.0);
|
|
correct3 = ref_func(-0.0, 0.0);
|
|
correct4 = ref_func(0.0, -0.0);
|
|
correct5 = ref_func(-0.0, -0.0);
|
|
|
|
// Per section 10 paragraph 6, accept any
|
|
// result if an input or output is a
|
|
// infinity or NaN or overflow As per
|
|
// OpenCL 2.0 spec, section 5.8.4.3,
|
|
// enabling fast-relaxed-math mode also
|
|
// enables -cl-finite-math-only
|
|
// optimization. This optimization allows to
|
|
// assume that arguments and results are not
|
|
// NaNs or +/-INFs. Hence, accept any result
|
|
// if inputs or results are NaNs or INFs.
|
|
if (relaxedMode || skipNanInf)
|
|
{
|
|
if (fetestexcept(FE_OVERFLOW)
|
|
&& skipNanInf)
|
|
continue;
|
|
|
|
// Note: no double rounding here.
|
|
// Reference functions calculate in
|
|
// single precision.
|
|
if (IsFloatInfinity(correct2)
|
|
|| IsFloatNaN(correct2)
|
|
|| IsFloatInfinity(correct3)
|
|
|| IsFloatNaN(correct3)
|
|
|| IsFloatInfinity(correct4)
|
|
|| IsFloatNaN(correct4)
|
|
|| IsFloatInfinity(correct5)
|
|
|| IsFloatNaN(correct5))
|
|
continue;
|
|
}
|
|
|
|
err2 = Ulp_Error(test, correct2);
|
|
err3 = Ulp_Error(test, correct3);
|
|
err4 = Ulp_Error(test, correct4);
|
|
err5 = Ulp_Error(test, correct5);
|
|
fail = fail
|
|
&& ((!(fabsf(err2) <= ulps))
|
|
&& (!(fabsf(err3) <= ulps))
|
|
&& (!(fabsf(err4) <= ulps))
|
|
&& (!(fabsf(err5) <= ulps)));
|
|
if (fabsf(err2) < fabsf(err)) err = err2;
|
|
if (fabsf(err3) < fabsf(err)) err = err3;
|
|
if (fabsf(err4) < fabsf(err)) err = err4;
|
|
if (fabsf(err5) < fabsf(err)) err = err5;
|
|
|
|
// retry per section 6.5.3.4
|
|
if (IsFloatResultSubnormal(correct2, ulps)
|
|
|| IsFloatResultSubnormal(correct3,
|
|
ulps)
|
|
|| IsFloatResultSubnormal(correct4,
|
|
ulps)
|
|
|| IsFloatResultSubnormal(correct5,
|
|
ulps))
|
|
{
|
|
fail = fail && (test != 0.0f);
|
|
if (!fail) err = 0.0f;
|
|
}
|
|
}
|
|
}
|
|
else if (IsFloatSubnormal(s2[j]))
|
|
{
|
|
double correct2, correct3;
|
|
float err2, err3;
|
|
|
|
if (skipNanInf) feclearexcept(FE_OVERFLOW);
|
|
|
|
correct2 = ref_func(s[j], 0.0);
|
|
correct3 = ref_func(s[j], -0.0);
|
|
|
|
// Per section 10 paragraph 6, accept any result
|
|
// if an input or output is a infinity or NaN or
|
|
// overflow As per OpenCL 2.0 spec,
|
|
// section 5.8.4.3, enabling fast-relaxed-math
|
|
// mode also enables -cl-finite-math-only
|
|
// optimization. This optimization allows to
|
|
// assume that arguments and results are not
|
|
// NaNs or +/-INFs. Hence, accept any result if
|
|
// inputs or results are NaNs or INFs.
|
|
if (relaxedMode || skipNanInf)
|
|
{
|
|
// Note: no double rounding here. Reference
|
|
// functions calculate in single precision.
|
|
if (overflow[j] && skipNanInf) continue;
|
|
|
|
if (IsFloatInfinity(correct2)
|
|
|| IsFloatNaN(correct2)
|
|
|| IsFloatInfinity(correct3)
|
|
|| IsFloatNaN(correct3))
|
|
continue;
|
|
}
|
|
|
|
err2 = Ulp_Error(test, correct2);
|
|
err3 = Ulp_Error(test, correct3);
|
|
fail = fail
|
|
&& ((!(fabsf(err2) <= ulps))
|
|
&& (!(fabsf(err3) <= ulps)));
|
|
if (fabsf(err2) < fabsf(err)) err = err2;
|
|
if (fabsf(err3) < fabsf(err)) err = err3;
|
|
|
|
// retry per section 6.5.3.4
|
|
if (IsFloatResultSubnormal(correct2, ulps)
|
|
|| IsFloatResultSubnormal(correct3, ulps))
|
|
{
|
|
fail = fail && (test != 0.0f);
|
|
if (!fail) err = 0.0f;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
if (fabsf(err) > tinfo->maxError)
|
|
{
|
|
tinfo->maxError = fabsf(err);
|
|
tinfo->maxErrorValue = s[j];
|
|
tinfo->maxErrorValue2 = s2[j];
|
|
}
|
|
if (fail)
|
|
{
|
|
vlog_error(
|
|
"\nERROR: %s%s: %f ulp error at {%a (0x%x), %a "
|
|
"(0x%x)}: *%a vs. %a (0x%8.8x) at index: %zu\n",
|
|
name, sizeNames[k], err, s[j], ((cl_uint *)s)[j],
|
|
s2[j], ((cl_uint *)s2)[j], r[j], test,
|
|
((cl_uint *)&test)[0], j);
|
|
return -1;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
if (isFDim && gIsInRTZMode) (void)set_round(oldRoundMode, kfloat);
|
|
|
|
for (auto 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:%10zu ulps:%5.3f "
|
|
"ThreadCount:%2u\n",
|
|
base, job->step, job->scale, buffer_elements, job->ulps,
|
|
job->threadCount);
|
|
}
|
|
else
|
|
{
|
|
vlog(".");
|
|
}
|
|
fflush(stdout);
|
|
}
|
|
|
|
return CL_SUCCESS;
|
|
}
|
|
|
|
} // anonymous namespace
|
|
|
|
int TestFunc_Float_Float_Float(const Func *f, MTdata d, bool relaxedMode)
|
|
{
|
|
TestInfo test_info{};
|
|
cl_int error;
|
|
float maxError = 0.0f;
|
|
double maxErrorVal = 0.0;
|
|
double maxErrorVal2 = 0.0;
|
|
|
|
logFunctionInfo(f->name, sizeof(cl_float), relaxedMode);
|
|
|
|
// Init test_info
|
|
test_info.threadCount = GetThreadCount();
|
|
test_info.subBufferSize = BUFFER_SIZE
|
|
/ (sizeof(cl_float) * RoundUpToNextPowerOfTwo(test_info.threadCount));
|
|
test_info.scale = getTestScale(sizeof(cl_float));
|
|
|
|
test_info.step = (cl_uint)test_info.subBufferSize * test_info.scale;
|
|
if (test_info.step / test_info.subBufferSize != test_info.scale)
|
|
{
|
|
// there was overflow
|
|
test_info.jobCount = 1;
|
|
}
|
|
else
|
|
{
|
|
test_info.jobCount = (cl_uint)((1ULL << 32) / test_info.step);
|
|
}
|
|
|
|
test_info.f = f;
|
|
test_info.ulps = gIsEmbedded ? f->float_embedded_ulps : f->float_ulps;
|
|
test_info.ftz =
|
|
f->ftz || gForceFTZ || 0 == (CL_FP_DENORM & gFloatCapabilities);
|
|
test_info.relaxedMode = relaxedMode;
|
|
test_info.isFDim = 0 == strcmp("fdim", f->nameInCode);
|
|
test_info.skipNanInf = test_info.isFDim && !gInfNanSupport;
|
|
test_info.isNextafter = 0 == strcmp("nextafter", f->nameInCode);
|
|
|
|
test_info.tinfo.resize(test_info.threadCount);
|
|
for (cl_uint i = 0; i < test_info.threadCount; i++)
|
|
{
|
|
cl_buffer_region region = {
|
|
i * test_info.subBufferSize * sizeof(cl_float),
|
|
test_info.subBufferSize * sizeof(cl_float)
|
|
};
|
|
test_info.tinfo[i].inBuf =
|
|
clCreateSubBuffer(gInBuffer, CL_MEM_READ_ONLY,
|
|
CL_BUFFER_CREATE_TYPE_REGION, ®ion, &error);
|
|
if (error || NULL == test_info.tinfo[i].inBuf)
|
|
{
|
|
vlog_error("Error: Unable to create sub-buffer of gInBuffer for "
|
|
"region {%zd, %zd}\n",
|
|
region.origin, region.size);
|
|
return error;
|
|
}
|
|
test_info.tinfo[i].inBuf2 =
|
|
clCreateSubBuffer(gInBuffer2, CL_MEM_READ_ONLY,
|
|
CL_BUFFER_CREATE_TYPE_REGION, ®ion, &error);
|
|
if (error || NULL == test_info.tinfo[i].inBuf2)
|
|
{
|
|
vlog_error("Error: Unable to create sub-buffer of gInBuffer2 for "
|
|
"region {%zd, %zd}\n",
|
|
region.origin, region.size);
|
|
return error;
|
|
}
|
|
|
|
for (auto j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++)
|
|
{
|
|
test_info.tinfo[i].outBuf[j] = clCreateSubBuffer(
|
|
gOutBuffer[j], CL_MEM_WRITE_ONLY, CL_BUFFER_CREATE_TYPE_REGION,
|
|
®ion, &error);
|
|
if (error || NULL == test_info.tinfo[i].outBuf[j])
|
|
{
|
|
vlog_error("Error: Unable to create sub-buffer of "
|
|
"gOutBuffer[%d] for region {%zd, %zd}\n",
|
|
(int)j, region.origin, region.size);
|
|
return error;
|
|
}
|
|
}
|
|
test_info.tinfo[i].tQueue =
|
|
clCreateCommandQueue(gContext, gDevice, 0, &error);
|
|
if (NULL == test_info.tinfo[i].tQueue || error)
|
|
{
|
|
vlog_error("clCreateCommandQueue failed. (%d)\n", error);
|
|
return error;
|
|
}
|
|
|
|
test_info.tinfo[i].d = MTdataHolder(genrand_int32(d));
|
|
}
|
|
|
|
// Init the kernels
|
|
BuildKernelInfo build_info{ test_info.threadCount, test_info.k,
|
|
test_info.programs, f->nameInCode,
|
|
relaxedMode };
|
|
if ((error = ThreadPool_Do(BuildKernelFn,
|
|
gMaxVectorSizeIndex - gMinVectorSizeIndex,
|
|
&build_info)))
|
|
return error;
|
|
|
|
// Run the kernels
|
|
if (!gSkipCorrectnessTesting)
|
|
{
|
|
error = ThreadPool_Do(Test, test_info.jobCount, &test_info);
|
|
if (error) return error;
|
|
|
|
// Accumulate the arithmetic errors
|
|
for (cl_uint i = 0; i < test_info.threadCount; i++)
|
|
{
|
|
if (test_info.tinfo[i].maxError > maxError)
|
|
{
|
|
maxError = test_info.tinfo[i].maxError;
|
|
maxErrorVal = test_info.tinfo[i].maxErrorValue;
|
|
maxErrorVal2 = test_info.tinfo[i].maxErrorValue2;
|
|
}
|
|
}
|
|
|
|
if (gWimpyMode)
|
|
vlog("Wimp pass");
|
|
else
|
|
vlog("passed");
|
|
|
|
vlog("\t%8.2f @ {%a, %a}", maxError, maxErrorVal, maxErrorVal2);
|
|
}
|
|
|
|
vlog("\n");
|
|
|
|
return CL_SUCCESS;
|
|
}
|