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/*=========================================================================
*
* Copyright NumFOCUS
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#include "itkMath.h"
#include "itkDomainThreader.h"
#include "itkThreadedIndexedContainerPartitioner.h"
#include "itkCompensatedSummation.h"
#include <iostream>
#include <iomanip>
/*
* This test demonstrates the variance in output when the same operation is
* performed with different numbers of threads, and the utility of the
* CompensatedSummation class for summing the per-thread output of
* multi-threaded operation to reduce the variance. The variance is a
* result of different floating-point rounding that occurs when
* different numbers of threads are used.
*/
class CompensatedSummationTest2Associate
{
public:
using Self = CompensatedSummationTest2Associate;
// Nested class holds the domain threader
class TestDomainThreader : public itk::DomainThreader<itk::ThreadedIndexedContainerPartitioner, Self>
{
public:
ITK_DISALLOW_COPY_AND_MOVE(TestDomainThreader);
using Self = TestDomainThreader;
using Superclass = itk::DomainThreader<itk::ThreadedIndexedContainerPartitioner, Self>;
using Pointer = itk::SmartPointer<Self>;
using ConstPointer = itk::SmartPointer<const Self>;
using DomainPartitionerType = Superclass::DomainPartitionerType;
using DomainType = Superclass::DomainType;
itkNewMacro(Self);
protected:
TestDomainThreader() = default;
private:
void
BeforeThreadedExecution() override
{
const itk::ThreadIdType numWorkUnitsUsed = this->GetNumberOfWorkUnitsUsed();
this->m_PerThreadCompensatedSum.resize(numWorkUnitsUsed);
for (itk::ThreadIdType i = 0; i < numWorkUnitsUsed; ++i)
{
this->m_PerThreadCompensatedSum[i].ResetToZero();
}
}
void
ThreadedExecution(const DomainType & subdomain, const itk::ThreadIdType threadId) override
{
for (DomainType::IndexValueType i = subdomain[0]; i <= subdomain[1]; ++i)
{
double value = 1.0 / 7;
this->m_PerThreadCompensatedSum[threadId].AddElement(value);
}
}
void
AfterThreadedExecution() override
{
this->m_Associate->m_UncompensatedSumOfThreads = 0.0;
this->m_Associate->m_CompensatedSumOfThreads.ResetToZero();
for (itk::ThreadIdType i = 0, numWorkUnitsUsed = this->GetNumberOfWorkUnitsUsed(); i < numWorkUnitsUsed; ++i)
{
double sum = this->m_PerThreadCompensatedSum[i].GetSum();
std::cout << i << ": " << sum << std::endl;
this->m_Associate->m_CompensatedSumOfThreads.AddElement(sum);
this->m_Associate->m_UncompensatedSumOfThreads += sum;
}
}
std::vector<itk::CompensatedSummation<double>> m_PerThreadCompensatedSum;
}; // end TestDomainThreader class
CompensatedSummationTest2Associate()
{
m_TestDomainThreader = TestDomainThreader::New();
m_ClassDescriptor = "enclosing class";
m_UncompensatedSumOfThreads = 0.0;
}
double
GetCompensatedSumOfThreads()
{
return this->m_CompensatedSumOfThreads.GetSum();
}
double
GetUncompensatedSumOfThreads() const
{
return this->m_UncompensatedSumOfThreads;
}
TestDomainThreader *
GetDomainThreader()
{
return m_TestDomainThreader.GetPointer();
}
void
Execute(const TestDomainThreader::DomainType & completeDomain)
{
m_TestDomainThreader->Execute(this, completeDomain);
}
private:
TestDomainThreader::Pointer m_TestDomainThreader;
std::string m_ClassDescriptor;
itk::CompensatedSummation<double> m_CompensatedSumOfThreads;
double m_UncompensatedSumOfThreads;
};
int
itkCompensatedSummationTest2(int, char *[])
{
CompensatedSummationTest2Associate enclosingClass;
CompensatedSummationTest2Associate::TestDomainThreader::Pointer domainThreader = enclosingClass.GetDomainThreader();
/* Check # of threads */
std::cout << "GetGlobalMaximumNumberOfThreads: "
<< domainThreader->GetMultiThreader()->GetGlobalMaximumNumberOfThreads() << std::endl;
std::cout << "GetGlobalDefaultNumberOfThreads: "
<< domainThreader->GetMultiThreader()->GetGlobalDefaultNumberOfThreads() << std::endl;
using DomainType = CompensatedSummationTest2Associate::TestDomainThreader::DomainType;
DomainType domain;
itk::ThreadIdType maxNumberOfThreads = domainThreader->GetMultiThreader()->GetGlobalMaximumNumberOfThreads();
domain[0] = 0;
domain[1] = maxNumberOfThreads * 10000;
/* Test with single thread. We should get the same result. */
itk::ThreadIdType numberOfThreads = 1;
domainThreader->SetMaximumNumberOfThreads(numberOfThreads);
domainThreader->SetNumberOfWorkUnits(numberOfThreads);
std::cout << "Testing with " << numberOfThreads << " threads and domain " << domain << " ..." << std::endl;
/* Execute */
enclosingClass.Execute(domain);
/* Did we use as many threads as requested? */
std::cout << "Requested numberOfThreads: " << numberOfThreads << std::endl
<< "actual: threader->GetNumberOfWorkUnitsUsed(): " << domainThreader->GetNumberOfWorkUnitsUsed() << "\n\n"
<< std::endl;
/* Check results */
if (itk::Math::NotAlmostEquals(enclosingClass.GetCompensatedSumOfThreads(),
enclosingClass.GetUncompensatedSumOfThreads()))
{
std::cerr << std::setprecision(20) << "Error. Expected the sum to be the same for compensated and uncompensated."
<< " Instead, got " << enclosingClass.GetCompensatedSumOfThreads() << " and "
<< enclosingClass.GetUncompensatedSumOfThreads() << std::endl
<< "Difference: "
<< enclosingClass.GetCompensatedSumOfThreads() - enclosingClass.GetUncompensatedSumOfThreads()
<< std::endl;
return EXIT_FAILURE;
}
/* Store result as reference */
double referenceSum = enclosingClass.GetCompensatedSumOfThreads();
/* Test with maximum threads. We need at least three threads to see a difference. */
if (domainThreader->GetMultiThreader()->GetGlobalMaximumNumberOfThreads() > 2)
{
domainThreader->SetMaximumNumberOfThreads(maxNumberOfThreads);
domainThreader->SetNumberOfWorkUnits(maxNumberOfThreads);
std::cout << "Testing with " << maxNumberOfThreads << " threads and domain " << domain << " ..." << std::endl;
/* Execute */
enclosingClass.Execute(domain);
/* Check number of threads used */
if (domainThreader->GetNumberOfWorkUnitsUsed() != maxNumberOfThreads)
{
std::cerr << "Error: Expected to use " << maxNumberOfThreads << "threads, but used "
<< domainThreader->GetNumberOfWorkUnitsUsed() << '.' << std::endl;
return EXIT_FAILURE;
}
std::cout << "# of digits precision in double: " << std::numeric_limits<double>::digits10 << std::endl;
std::cout << std::setprecision(100) << "Reference: " << referenceSum << std::endl
<< "Compensated: " << enclosingClass.GetCompensatedSumOfThreads() << std::endl
<< "Uncompensated: " << enclosingClass.GetUncompensatedSumOfThreads() << std::endl
<< "Difference: "
<< enclosingClass.GetCompensatedSumOfThreads() - enclosingClass.GetUncompensatedSumOfThreads()
<< std::endl;
/* Check that the compensated result is not further from reference than
* uncompensated.
* Generally we see the compensated sum closer, but on a few platforms the
* sums are equal. This could be because of differences in compiler
* optimizations that were not handled by the CompensatedSummation class
* pragmas, or perhaps because of differences in math coprocessors, or
* something else. It's not clear. */
if (itk::Math::abs(referenceSum - enclosingClass.GetCompensatedSumOfThreads()) >
itk::Math::abs(referenceSum - enclosingClass.GetUncompensatedSumOfThreads()))
{
std::cerr << "Error. Expected the compensated sum of threads to be closer "
<< "to reference than the uncompensated sum, or the same value. " << std::endl;
return EXIT_FAILURE;
}
}
else
{
std::cout << "No multi-threading available, or too few threads available. " << std::endl;
}
return EXIT_SUCCESS;
}
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