Hi,
I suspect that your timings include kernel compilation times. Please
have a 'warmup' call of norm_1() outside your timing region.
Which GPU do you have on your Macbook Pro?
Best regards,
Karli
On 02/17/2017 05:27 PM, Sensei wrote:
> Hi!
>
> I am new to the OpenCL/GPU world, and I probably expected too much from
> it. I am computing the norm_1 of a vector, on the CPU and GPU, and I had
> these results:
>
> *Platform Apple*
> *Version OpenCL 1.2 (Jan 4 2017 22:35:59)*
> **
> *> Device type CPU*
> *Version OpenCL 1.2 (Jan 4 2017 22:35:59)*
> *> Device type GPU*
> *Version OpenCL 1.2 (Jan 4 2017 22:35:59)*
> *
> *
> *STARTING, TIMES ARE IN MILLISECONDS*
> *
> *
> *Reserving CPU vector *
> *Reserving CPU vector 16*
> **
> *Filling CPU vector *
> *Filling CPU vector 9*
> **
> *Reserving GPU vector *
> *Reserving GPU vector 82*
> **
> *Copying to GPU *
> *Copying to GPU 158310*
> **
> *Computing norm_1 on GPU *
> *Computing norm_1 on GPU 333*
> **
> *Computing norm_1 on CPU *
> *Computing norm_1 on CPU 8*
> **
> *GPU: 5e+11 CPU: 5.00000e+11*
> *Program ended with exit code: 0*
> *
> *
> As you can see, the GPU times are waaaaay higher than the CPU ones. My
> code is really simple, and I am following the recommended conduct to
> build values on the CPU and then copy them.
>
> Is this bad performance due to my platform? I am running on a MacBook
> Pro now. My code follows.
>
> Thanks!
>
>
> #include <iostream>
> #include <vector>
> #include <algorithm>
> #include <cstdlib>
> #include <numeric>
> #include <chrono>
>
> #define CL_USE_DEPRECATED_OPENCL_1_1_APIS
> #define __CL_ENABLE_EXCEPTIONS
>
> #define VIENNACL_WITH_OPENCL
>
> #include "cl.hpp"
> #include "viennacl/scalar.hpp"
> #include "viennacl/vector.hpp"
> #include "viennacl/ocl/backend.hpp"
> #include "viennacl/linalg/norm_1.hpp"
>
> intmain(intargc, constchar* argv[])
> {
> // This is what vienna sees
> autoviennaplatforms = viennacl::ocl::get_platforms();
> autoviennadevices = viennacl::ocl::platform().devices();
>
>
>
> // See what standard OpenCL sees
> std::vector<cl::Platform> platforms;
>
>
>
> // Get platform
> cl::Platform::get(&platforms);
>
> // Temp
> std::strings;
>
>
>
> // Where the GPU lies
> cl::Devicegpudevice;
>
>
>
> // Found a GPU
> boolgpufound = false;
>
>
>
> // See if we have a GPU
> for(autop : platforms)
> {
> s.clear();
> p.getInfo(CL_PLATFORM_NAME, &s);
> std::cout<< "Platform "<< s << std::endl;
>
> s.clear();
> p.getInfo(CL_PLATFORM_VERSION, &s);
> std::cout<< "Version "<< s << std::endl;
>
> std::cout<< std::endl;
>
>
>
> std::vector<cl::Device> devices;
>
> p.getDevices(CL_DEVICE_TYPE_ALL, &devices);
>
>
>
> for(autod : devices)
> {
> std::size_ti = 4;
> d.getInfo(CL_DEVICE_TYPE, &i);
>
> std::cout<< "> Device type "<<
> (i & CL_DEVICE_TYPE_CPU? "CPU": "") <<
> (i & CL_DEVICE_TYPE_GPU? "GPU": "") <<
> (i & CL_DEVICE_TYPE_ACCELERATOR? "ACCELERATOR":
> "") <<
> std::endl;
>
>
>
> if(i & CL_DEVICE_TYPE_GPU)
> {
> gpudevice = d;
> gpufound = true;
> }
>
>
>
> std::cout<< "Version "<< s << std::endl;
>
> }
> }
>
>
>
> if(!gpufound)
> {
> std::cout<< "NO GPU FOUND. ABORTING."<< std::endl;
> return1;
> }
>
> // Size
> intsize = 1* 1000* 1000;
>
> // Measuring time
> autostart = std::chrono::steady_clock::now();
>
> std::cout<< std::endl<< "STARTING, TIMES ARE IN MILLISECONDS"<<
> std::endl << std::endl;
>
>
>
> std::cout<< "Reserving CPU vector "<< std::endl;
> start = std::chrono::steady_clock::now();
> std::vector<double> cpuv;
> cpuv.resize(size);
> std::cout<< "Reserving CPU vector "<<
> std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::steady_clock::now()-start).count()
> << std::endl<< std::endl;
>
>
>
> std::cout<< "Filling CPU vector " << std::endl;
> start = std::chrono::steady_clock::now();
> std::iota(cpuv.begin(), cpuv.end(), 1.0);
> std::cout<< "Filling CPU vector "<<
> std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::steady_clock::now()-start).count()
> << std::endl<< std::endl;
>
>
>
> std::cout<< "Reserving GPU vector " << std::endl;
> start = std::chrono::steady_clock::now();
> viennacl::vector<float> gpuv;
> gpuv.resize(size);
> std::cout<< "Reserving GPU vector "<<
> std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::steady_clock::now()-start).count()
> << std::endl<< std::endl;
>
>
>
> std::cout<< "Copying to GPU " << std::endl;
> start = std::chrono::steady_clock::now();
> std::copy(cpuv.begin(), cpuv.end(), gpuv.begin());
> std::cout<< "Copying to GPU "<<
> std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::steady_clock::now()-start).count()
> << std::endl<< std::endl;
>
> std::cout<< "Computing norm_1 on GPU " << std::endl;
> start = std::chrono::steady_clock::now();
> doublegpunorm1 = viennacl::linalg::norm_1(gpuv);
> std::cout<< "Computing norm_1 on GPU "<<
> std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::steady_clock::now()-start).count()
> << std::endl<< std::endl;
>
> std::cout<< "Computing norm_1 on CPU " << std::endl;
> start = std::chrono::steady_clock::now();
> doublecpunorm1 = std::accumulate(cpuv.begin(), cpuv.end(), 0.0,
> [](doublea, doubleb){ returna +
> std::abs(b); });
> std::cout<< "Computing norm_1 on CPU "<<
> std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::steady_clock::now()-start).count()
> << std::endl<< std::endl;
>
>
>
> std::cout<< "GPU: "<< gpunorm1 << " CPU: "<< cpunorm1 << std::endl;
>
>
>
> return0;
> }
>
>
>
>
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