Movatterモバイル変換

[0]ホーム
URL:

Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

 Sign up
Appearance settings

A modern Fortran abstraction layer for OpenCL

License

NotificationsYou must be signed in to change notification settings

LKedward/focal

Repository files navigation

License: MITfpm testcodecov

A modern Fortran abstraction layer for OpenCL

Focal is a module library which wraps calls to the OpenCL runtime API (usingclfortran) with a higher abstraction level appropriate to the Fortran language.

The goal of Focal is to provide a concise and accessible Fortran interface to the OpenCL API while retaining the full functionality thereof.This is desirable in Fortran which as a language provides a higher level of abstraction than C; importantly this allows scientists and engineers to focus on their domain specific problem rather than details of low-level implementation.

Key features:

  • Removes use of c pointers to call OpenCL API
  • Provides a level of type safety using typed buffer objects
  • Decreases verbosity of OpenCL API calls while still providing the same functionality
  • Abstracts away low level details, such as size in bytes
  • Contains built-in customisable error handling for all OpenCL API calls
  • Contains built-in 'debug' mode for checking program correctness
  • Contains build-in routines for collecting and presented profiling information

Project status: v1.0.1 stable release

Documentation:lkedward.github.io/focal-docs

License:MIT

Prerequisites:

Getting started

Quick example

The following fortran program calculates the sum of two large arrays using an OpenCL kernel.

program sum!! Focal exampleprogram: calculate the sum of two arrays on an OpenCL deviceuse Focalimplicit noneinteger,parameter:: Nelem=1E6           ! No. of array elementsreal,parameter:: sumVal=10.0            ! Target value for array suminteger:: i                                ! Counter variablecharacter(:), allocatable:: kernelSrc      ! Kernel source stringtype(fclDevice):: device                   ! Device objecttype(fclProgram):: prog                    ! Focalprogram objecttype(fclKernel):: sumKernel                ! Focal kernel objectreal:: array1(Nelem)                       ! Host array1real:: array2(Nelem)                       ! Host array2type(fclDeviceFloat):: array1_d            ! Device array1type(fclDeviceFloat):: array2_d            ! Device array2! Select device with most cores and create command queuedevice= fclInit(vendor='nvidia',sortBy='cores')call fclSetDefaultCommandQ(fclCreateCommandQ(device,enableProfiling=.true.))! Load kernel from file and compilecall fclSourceFromFile('examples/sum.cl',kernelSrc)prog= fclCompileProgram(kernelSrc)sumKernel= fclGetProgramKernel(prog,'sum')! Initialise device arrayscall fclInitBuffer(array1_d,Nelem)call fclInitBuffer(array2_d,Nelem)! Initialise host arraydatado i=1,Nelem  array1(i)= iend doarray2= sumVal- array1! Copydatato devicearray1_d= array1array2_d= array2! Set global work size equalto array length and launch kernelsumKernel%global_work_size(1)= Nelemcall sumKernel%launch(Nelem,array1_d,array2_d)! Copy result backto host andprintoutto checkarray2= array2_dwrite(*,*) array2(1), array2(size(array2,1))end program sum

Wheresum.cl contains the following openCL kernel:

__kernelvoidsum(constintnElem,const__globalfloat*v1,__globalfloat*v2){inti=get_global_id(0);if(i<nElem)v2[i]+=v1[i];}

Bundled third-party sources

The following open source libraries are used as dependencies and bundled in the repository (./external):

Acknowledgement

This work was funded by the MENtOR project, a UKVLN projectsupported by the Engineering and Physical Sciences ResearchCouncil (EPSRC) of the UK. Grant reference numberEP/S010378/1.

[8]ページ先頭
©2009-2025 Movatter.jp