[ITK-users] GPUDiscreteGaussian not working

Jim Miller millerjv at gmail.com
Tue Apr 15 18:40:10 EDT 2014


Does the test for GPUDiscreteGaussian run on your platform?

The test uses a pixel type of float. Your code does not. You might try float. 

The Gaussian filter will require much more GPU memory than the mean filter. How much memory does your GPU have?

Jim

> On Apr 15, 2014, at 11:18 AM, Jose Ignacio Prieto <joseignacio.prieto at gmail.com> wrote:
> 
> Hi all, I am having trouble using GPUdiscretegaussian. It works for me on CPU but GPU version gives output 0. I tried running the test code but no help. I do run GPUMean filter. My card is AMDw7000 and using opencl 1.2, itk 4.6
> 
> Here is the code and the output. The images are vtk files of 320x320x231, ushort.
> 
> /*=========================================================================
> *
> *  Copyright Insight Software Consortium
> *
> *  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
> *
> *         http://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 "itkImageFileReader.h"
> #include "itkImageFileWriter.h"
> 
> #include "itkGPUImage.h"
> #include "itkGPUKernelManager.h"
> #include "itkGPUContextManager.h"
> #include "itkGPUImageToImageFilter.h"
> #include "itkGPUNeighborhoodOperatorImageFilter.h"
> 
> #include "itkTimeProbe.h"
> #include "itkGaussianOperator.h"
> 
> #include "itkDiscreteGaussianImageFilter.h"
> #include "itkGPUDiscreteGaussianImageFilter.h"
> #include "itkMeanImageFilter.h"
> #include "itkGPUMeanImageFilter.h"
> 
> //  typedef float InputPixelType;
> //  typedef float OutputPixelType;
> typedef  short InputPixelType;
> typedef  short OutputPixelType;
> 
> typedef itk::GPUImage< InputPixelType,  3 >   InputImageType;
> typedef itk::GPUImage< OutputPixelType, 3 >   OutputImageType;
> 
> 
> 
> typedef itk::ImageFileReader< InputImageType  >  ReaderType;
> typedef itk::ImageFileWriter< OutputImageType >  WriterType;
> 
> 
> 
> int main(int argc, char *argv[])
> {
>     if(!itk::IsGPUAvailable())
>     {
>         std::cerr << "OpenCL-enabled GPU is not present." << std::endl;
>         return EXIT_FAILURE;
>     }
> 
>     if( argc <  3 )
>     {
>         std::cerr << "Error: missing arguments" << std::endl;
>         std::cerr << "inputfile outputfile [num_dimensions]" << std::endl;
>         return EXIT_FAILURE;
>     }
> 
>     std::string inFile( argv[1] );
>     std::string outFile( argv[2] );
> 
>     unsigned int dim = 3;
>     ReaderType::Pointer reader;
>     WriterType::Pointer writer;
>     reader = ReaderType::New();
>     writer = WriterType::New();
> 
>     reader->SetFileName( inFile );
>     writer->SetFileName( outFile );
> 
>     float variance = 4.0;
> 
>     // test 1~8 threads for CPU
>     int nThreads = 8;
> 
>     typedef itk::DiscreteGaussianImageFilter< InputImageType, OutputImageType> CPUFilterType;
>     CPUFilterType::Pointer CPUFilter = CPUFilterType::New();
>     itk::TimeProbe cputimer;
>     cputimer.Start();
>     CPUFilter->SetNumberOfThreads( nThreads );
>     CPUFilter->SetInput( reader->GetOutput() );
>     CPUFilter->SetMaximumKernelWidth(10);
>     CPUFilter->SetUseImageSpacingOff();
>     CPUFilter->SetVariance( variance );
>     CPUFilter->Update();
>     cputimer.Stop();
> 
> //    typedef itk::MeanImageFilter< InputImageType, OutputImageType> CPUFilterType;
> //    CPUFilterType::Pointer CPUFilter = CPUFilterType::New();
> //    itk::TimeProbe cputimer;
> //    cputimer.Start();
> //    CPUFilter->SetNumberOfThreads( nThreads );
> //    CPUFilter->SetInput( reader->GetOutput() );
> ////    CPUFilter->SetMaximumKernelWidth(10);
> ////    CPUFilter->SetUseImageSpacingOff();
> //    CPUFilter->SetRadius( variance );
> //    CPUFilter->Update();
> //    cputimer.Stop();
> 
>     std::cout << "CPU Gaussian Filter took " << cputimer.GetMean() << " seconds with "
>               << CPUFilter->GetNumberOfThreads() << " threads.\n" << std::endl;
> 
>     // -------
> 
>     typedef itk::GPUDiscreteGaussianImageFilter< InputImageType, OutputImageType> GPUFilterType;
>     GPUFilterType::Pointer GPUFilter = GPUFilterType::New();
>     itk::TimeProbe gputimer;
>     gputimer.Start();
>     GPUFilter->SetInput( reader->GetOutput() );
>     GPUFilter->SetVariance( variance );
>     GPUFilter->SetMaximumKernelWidth(10);
>     GPUFilter->SetUseImageSpacingOff();
> //    GPUFilter->DebugOn();
> //    GPUFilter->GPUEnabledOff();
>     GPUFilter->Print(std::cout);
>     GPUFilter->Update();
>     GPUFilter->GetOutput()->UpdateBuffers(); // synchronization point (GPU->CPU memcpy)
>     gputimer.Stop();
>     std::cout << "GPU Gaussian Filter took " << gputimer.GetMean() << " seconds.\n" << std::endl;
> 
> //    typedef itk::GPUMeanImageFilter< InputImageType, OutputImageType> GPUFilterType;
> //    GPUFilterType::Pointer GPUFilter = GPUFilterType::New();
> //    itk::TimeProbe gputimer;
> //    gputimer.Start();
> //    GPUFilter->SetInput( reader->GetOutput() );
> ////    GPUFilter->SetVariance( variance );
> ////    GPUFilter->SetMaximumKernelWidth(10);
> ////    GPUFilter->SetUseImageSpacingOff();
> ////    GPUFilter->DebugOn();
> ////    GPUFilter->Print(std::cout);
> //    GPUFilter->SetRadius( variance );
> //    GPUFilter->Update();
> //    GPUFilter->GetOutput()->UpdateBuffers(); // synchronization point (GPU->CPU memcpy)
> //    gputimer.Stop();
> //    std::cout << "GPU Gaussian Filter took " << gputimer.GetMean() << " seconds.\n" << std::endl;
> 
>     // ---------------
>     // RMS Error check
>     // ---------------
> 
>     double diff = 0;
>     unsigned int nPix = 0;
>     itk::ImageRegionIterator<OutputImageType> cit(CPUFilter->GetOutput(), CPUFilter->GetOutput()->GetLargestPossibleRegion());
>     itk::ImageRegionIterator<OutputImageType> git(GPUFilter->GetOutput(), GPUFilter->GetOutput()->GetLargestPossibleRegion());
> 
>     for(cit.GoToBegin(), git.GoToBegin(); !cit.IsAtEnd(); ++cit, ++git)
>     {
>         double err = (double)(cit.Get()) - (double)(git.Get());
>         //         if(err > 0.1 || (double)cit.Get() < 0.1) std::cout << "CPU : " << (double)(cit.Get()) << ", GPU : " << (double)(git.Get()) << std::endl;
>         diff += err*err;
>         nPix++;
>     }
> 
>     writer->SetInput( GPUFilter->GetOutput() );
> //    writer->SetInput( CPUFilter->GetOutput() );
>     writer->Update();
> 
>     if (nPix > 0)
>     {
>         double RMSError = sqrt( diff / (double)nPix );
>         std::cout << "RMS Error : " << RMSError << std::endl;
>         // the CPU filter operator has type double
>         // but the double precision is not well-supported on most GPUs
>         // and by most drivers at this time.  Therefore, the GPU filter
>         // operator has type float
>         // relax the RMS threshold here to allow for errors due to
>         // differences in precision
>         // NOTE:
>         //   a threshold of 1.2e-5 worked on linux and Mac, but not Windows
>         //   why?
>         double RMSThreshold = 1.7e-5;
>         if (vnl_math_isnan(RMSError))
>         {
>             std::cout << "RMS Error is NaN! nPix: " << nPix << std::endl;
>             return EXIT_FAILURE;
>         }
>         if (RMSError > RMSThreshold)
>         {
>             std::cout << "RMS Error exceeds threshold (" << RMSThreshold << ")" << std::endl;
>             return EXIT_FAILURE;
>         }
>     }
>     else
>     {
>         std::cout << "No pixels in output!" << std::endl;
>         return EXIT_FAILURE;
>     }
> 
> }
> 
> 
> OUTPUT
> 
> 
> Starting C:\DocsMaracuya\Build\Ejemplos\Gpu\GPUTest.exe...
> Platform : AMD Accelerated Parallel Processing
> Platform : AMD Accelerated Parallel Processing
> Pitcairn
> Maximum Work Item Sizes : { 256, 256, 256 }
> Maximum Work Group Size : 256
> Alignment in bits of the base address : 2048
> Smallest alignment in bytes for any data type : 128
> cl_khr_fp64 cl_amd_fp64 cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_int64_base_atomics cl_khr_int64_extended_atomics cl_khr_3d_image_writes cl_khr_byte_addressable_store cl_khr_gl_sharing cl_ext_atomic_counters_32 cl_amd_device_attribute_query cl_amd_vec3 cl_amd_printf cl_amd_media_ops cl_amd_media_ops2 cl_amd_popcnt cl_khr_d3d10_sharing cl_amd_bus_addressable_memory cl_amd_c1x_atomics
> CPU Gaussian Filter took 1.70355 seconds with 8 threads.
> 
> Defines: #define DIM_3
> #define INTYPE short
> #define OUTTYPE short
> #define OPTYPE short
> 
> Defines: #define DIM_3
> #define INTYPE short
> #define OUTTYPE short
> #define OPTYPE short
> 
> Defines: #define DIM_3
> #define INTYPE short
> #define OUTTYPE short
> #define OPTYPE short
> 
> GPUDiscreteGaussianImageFilter (0000000002205DF0)
> RTTI typeinfo: class itk::GPUDiscreteGaussianImageFilter<class itk::GPUImage<short,3>,class itk::GPUImage<short,3> >
> Reference Count: 1
> Modified Time: 560
> Debug: Off
> Object Name:
> Observers:
> none
> Inputs:
> Primary: (000000000216E560) *
> Indexed Inputs:
> 0: Primary (000000000216E560)
> Required Input Names: Primary
> NumberOfRequiredInputs: 1
> Outputs:
> Primary: (000000000218A070)
> Indexed Outputs:
> 0: Primary (000000000218A070)
> NumberOfRequiredOutputs: 1
> Number Of Threads: 8
> ReleaseDataFlag: Off
> ReleaseDataBeforeUpdateFlag: Off
> AbortGenerateData: Off
> Progress: 0
> Multithreader:
> RTTI typeinfo: class itk::MultiThreader
> Reference Count: 1
> Modified Time: 499
> Debug: Off
> Object Name:
> Observers:
> none
> Thread Count: 8
> Global Maximum Number Of Threads: 128
> Global Default Number Of Threads: 8
> CoordinateTolerance: 1e-006
> DirectionTolerance: 1e-006
> Variance: [4, 4, 4]
> MaximumError: [0.01, 0.01, 0.01]
> MaximumKernelWidth: 10
> FilterDimensionality: 3
> UseImageSpacing: 0
> InternalNumberOfStreamDivisions: 9
> GPU: Enabled
> GPU Gaussian Filter took 0.111351 seconds.
> 
> RMS Error : 26.4279
> RMS Error exceeds threshold (1.7e-005)
> C:\DocsMaracuya\Build\Ejemplos\Gpu\GPUTest.exe exited with code 1
> 
> 
> -- 
> José Ignacio Prieto
> celular(nuevo): 94348182
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