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Avoid manual memory management (#1260)

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* Avoid manual memory management

Prefer std::vector over malloc and free. This will allow removing goto
statements by leveraging RAII.

Use appropriate type (bool) to store overflow predicates and allocate
std::vector<bool> of appropriate sizes: before this change the
allocation was unnecessary bigger than required.

No longer attempt to catch "out of host memory" issues, given that in
such situation it is generally not possible to cleanly report an error.
Rely on std::bad_alloc exception to report such issues.

Introduce a new header for common code in the math_brute_force
component. It is currently complementary to utility.h and is expected to
hold cleaned up content extracted from future refactoring operations.

List all headers as source in CMake for better compatibility with IDEs.

Signed-off-by: Marco Antognini <marco.antognini@arm.com>

* Remove manual or unnecessary memset

In order to use non-POD types as fields of TestInfo, memset must be
replaced with a compatible zero-initialisation.

Remove an unnecessary memset in MakeKernels.

Signed-off-by: Marco Antognini <marco.antognini@arm.com>
This commit is contained in:
Marco Antognini
2021-05-24 16:34:54 +01:00
committed by GitHub
parent a08cacc673
commit ed839ebf10
15 changed files with 366 additions and 581 deletions
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76
test_conformance/math_brute_force/binary_double.cpp
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@@ -14,6 +14,7 @@
// limitations under the License.
//
#include "common.h"
#include "function_list.h"
#include "test_functions.h"
#include "utility.h"
@@ -115,7 +116,7 @@ struct BuildKernelInfo
{
cl_uint offset; // the first vector size to build
cl_uint kernel_count;
cl_kernel **kernels;
KernelMatrix &kernels;
cl_program *programs;
const char *nameInCode;
bool relaxedMode; // Whether to build with -cl-fast-relaxed-math.
@@ -126,7 +127,8 @@ cl_int BuildKernelFn(cl_uint job_id, cl_uint thread_id UNUSED, void *p)
BuildKernelInfo *info = (BuildKernelInfo *)p;
cl_uint i = info->offset + job_id;
return BuildKernel(info->nameInCode, i, info->kernel_count,
info->kernels[i], info->programs + i, info->relaxedMode);
info->kernels[i].data(), info->programs + i,
info->relaxedMode);
}
// Thread specific data for a worker thread
@@ -149,11 +151,14 @@ struct TestInfo
size_t subBufferSize; // Size of the sub-buffer in elements
const Func *f; // A pointer to the function info
cl_program programs[VECTOR_SIZE_COUNT]; // programs for various vector sizes
cl_kernel
*k[VECTOR_SIZE_COUNT]; // arrays of thread-specific kernels for each
// worker thread: k[vector_size][thread_id]
ThreadInfo *
tinfo; // An array of thread specific information for each worker thread
// Thread-specific kernels for each vector size:
// k[vector_size][thread_id]
KernelMatrix k;
// Array of thread specific information
std::vector<ThreadInfo> tinfo;
cl_uint threadCount; // Number of worker threads
cl_uint jobCount; // Number of jobs
cl_uint step; // step between each chunk and the next.
@@ -284,11 +289,11 @@ constexpr size_t specialValuesCount =
cl_int Test(cl_uint job_id, cl_uint thread_id, void *data)
{
const TestInfo *job = (const TestInfo *)data;
TestInfo *job = (TestInfo *)data;
size_t buffer_elements = job->subBufferSize;
size_t buffer_size = buffer_elements * sizeof(cl_double);
cl_uint base = job_id * (cl_uint)job->step;
ThreadInfo *tinfo = job->tinfo + thread_id;
ThreadInfo *tinfo = &(job->tinfo[thread_id]);
float ulps = job->ulps;
dptr func = job->f->dfunc;
int ftz = job->ftz;
@@ -647,7 +652,7 @@ exit:
int TestFunc_Double_Double_Double(const Func *f, MTdata d, bool relaxedMode)
{
TestInfo test_info;
TestInfo test_info{};
cl_int error;
float maxError = 0.0f;
double maxErrorVal = 0.0;
@@ -656,7 +661,6 @@ int TestFunc_Double_Double_Double(const Func *f, MTdata d, bool relaxedMode)
logFunctionInfo(f->name, sizeof(cl_double), relaxedMode);
// Init test_info
memset(&test_info, 0, sizeof(test_info));
test_info.threadCount = GetThreadCount();
test_info.subBufferSize = BUFFER_SIZE
/ (sizeof(cl_double) * RoundUpToNextPowerOfTwo(test_info.threadCount));
@@ -685,27 +689,10 @@ int TestFunc_Double_Double_Double(const Func *f, MTdata d, bool relaxedMode)
// every thread
for (auto i = gMinVectorSizeIndex; i < gMaxVectorSizeIndex; i++)
{
size_t array_size = test_info.threadCount * sizeof(cl_kernel);
test_info.k[i] = (cl_kernel *)malloc(array_size);
if (NULL == test_info.k[i])
{
vlog_error("Error: Unable to allocate storage for kernels!\n");
error = CL_OUT_OF_HOST_MEMORY;
goto exit;
}
memset(test_info.k[i], 0, array_size);
test_info.k[i].resize(test_info.threadCount, nullptr);
}
test_info.tinfo =
(ThreadInfo *)malloc(test_info.threadCount * sizeof(*test_info.tinfo));
if (NULL == test_info.tinfo)
{
vlog_error(
"Error: Unable to allocate storage for thread specific data.\n");
error = CL_OUT_OF_HOST_MEMORY;
goto exit;
}
memset(test_info.tinfo, 0,
test_info.threadCount * sizeof(*test_info.tinfo));
test_info.tinfo.resize(test_info.threadCount, ThreadInfo{});
for (cl_uint i = 0; i < test_info.threadCount; i++)
{
cl_buffer_region region = {
@@ -802,27 +789,20 @@ exit:
for (auto i = gMinVectorSizeIndex; i < gMaxVectorSizeIndex; i++)
{
clReleaseProgram(test_info.programs[i]);
if (test_info.k[i])
for (auto &kernel : test_info.k[i])
{
for (cl_uint j = 0; j < test_info.threadCount; j++)
clReleaseKernel(test_info.k[i][j]);
free(test_info.k[i]);
clReleaseKernel(kernel);
}
}
if (test_info.tinfo)
{
for (cl_uint i = 0; i < test_info.threadCount; i++)
{
free_mtdata(test_info.tinfo[i].d);
clReleaseMemObject(test_info.tinfo[i].inBuf);
clReleaseMemObject(test_info.tinfo[i].inBuf2);
for (auto j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++)
clReleaseMemObject(test_info.tinfo[i].outBuf[j]);
clReleaseCommandQueue(test_info.tinfo[i].tQueue);
}
free(test_info.tinfo);
for (auto &threadInfo : test_info.tinfo)
{
free_mtdata(threadInfo.d);
clReleaseMemObject(threadInfo.inBuf);
clReleaseMemObject(threadInfo.inBuf2);
for (auto j = gMinVectorSizeIndex; j < gMaxVectorSizeIndex; j++)
clReleaseMemObject(threadInfo.outBuf[j]);
clReleaseCommandQueue(threadInfo.tQueue);
}
return error;