Significations et usages de OpenCL

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OpenCL (Open Computing Language) is a framework for writing programs that execute across heterogeneous platforms consisting of CPUs, GPUs, and other processors. OpenCL includes a language (based on C99) for writing kernels (functions that execute on OpenCL devices), plus APIs that are used to define and then control the platforms. OpenCL provides parallel computing using task-based and data-based parallelism.

OpenCL is analogous to the open industry standards OpenGL and OpenAL, for 3D graphics and computer audio, respectively. OpenCL extends the power of the GPU beyond graphics (GPGPU). OpenCL is managed by the non-profit technology consortium Khronos Group.

History

OpenCL was initially developed by Apple Inc., which holds trademark rights, and refined into an initial proposal in collaboration with technical teams at AMD, IBM, Intel, and Nvidia. Apple submitted this initial proposal to the Khronos Group. On June 16, 2008 the Khronos Compute Working Group was formed^[1] with representatives from CPU, GPU, embedded-processor, and software companies. This group worked for five months to finish the technical details of the specification for OpenCL 1.0 by November 18, 2008.^[2] This technical specification was reviewed by the Khronos members and approved for public release on December 8, 2008.^[3]

OpenCL 1.0 has been released with Mac OS X v10.6 ("Snow Leopard"). According to an Apple press release:^[4]

Snow Leopard further extends support for modern hardware with Open Computing Language (OpenCL), which lets any application tap into the vast gigaflops of GPU computing power previously available only to graphics applications. OpenCL is based on the C programming language and has been proposed as an open standard.

AMD has decided to support OpenCL (and DirectX 11) instead of the now deprecated Close to Metal in its Stream framework.^[5][6]RapidMind announced their adoption of OpenCL underneath their development platform, in order to support GPUs from multiple vendors with one interface.^[7]On December 9, 2008, Nvidia announced its intention to add full support for the OpenCL 1.0 specification to its GPU Computing Toolkit.^[8]. On October 30, 2009, IBM released its first OpenCL implementation as a part of the XL compilers^[9].

The OpenCL specification is under development at Khronos, which is open to any interested company to join.

Implementation

On December 10, 2008, AMD and Nvidia held the first public OpenCL demonstration, a 75-minute presentation at Siggraph Asia 2008. AMD showed a CPU-accelerated OpenCL demo explaining the scalability of OpenCL on one or more cores while Nvidia showed a GPU-accelerated demo.^[10][11]

On March 26, 2009, at GDC 2009, AMD and Havok demonstrated the first working implementation for OpenCL accelerating Havok Cloth on AMD Radeon HD 4000 series GPU.^[12]

On April 20, 2009, Nvidia announced the release of its OpenCL driver and SDK to developers participating in its OpenCL Early Access Program.^[13]

On August 5, 2009, AMD unveiled the first development tools for its OpenCL platform as part of its ATI Stream SDK v2.0 Beta Program.^[14]

On August 28, 2009, Apple released Mac OS X Snow Leopard, which contains a full implementation of OpenCL.^[15]OpenCL in Snow Leopard will initially be supported on the ATI Radeon HD 4850, ATI Radeon HD 4870 and NVIDIA's Geforce 8600M GT, GeForce 8800 GS, GeForce 8800 GT, GeForce 8800 GTS, Geforce 9400M, GeForce 9600M GT, GeForce GT 120, GeForce GT 130, GeForce GTX 285, Quadro FX 4800, and Quadro FX 5600.^[16]

On September 28, 2009, NVIDIA released its own OpenCL drivers and SDK implementation.

On October 13, 2009, AMD released the fourth beta of the ATI Stream SDK 2.0, which provides a complete OpenCL implementation on both R700/R800 GPUs and SSE3 capable CPUs. The SDK is available for both Linux and Windows. ^[17]

On November 26, 2009, NVIDIA released drivers for OpenCL 1.0 (rev 48).

The Apple^[18], Nvidia^[19], RapidMind^[20] and Mesa Gallium3D^[21] implementations of OpenCL are all based on the LLVM Compiler technology and use the Clang Compiler as its frontend.

On December 10, 2009, VIA released their first product supporting OpenCL 1.0 - ChromotionHD 2.0 video processor included in VN1000 chipset.^[22]

On December 21, 2009, AMD released the production version of the ATI Stream SDK 2.0,^[23] which provides OpenCL 1.0 support for R800 GPUs and beta support for R700 GPUs.

Example

This example will compute a Fast Fourier Transformation (FFT):^[24]<source lang="c">// create a compute context with GPU devicecontext = clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU, NULL, NULL, NULL);

// create a command queuequeue = clCreateCommandQueue(context, NULL, 0, NULL);

// allocate the buffer memory objectsmemobjs[0] = clCreateBuffer(context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, sizeof(float)*2*num_entries, srcA, NULL);memobjs[1] = clCreateBuffer(context, CL_MEM_READ_WRITE, sizeof(float)*2*num_entries, NULL, NULL);

// create the compute programprogram = clCreateProgramWithSource(context, 1, &fft1D_1024_kernel_src, NULL, NULL);

// build the compute program executableclBuildProgram(program, 0, NULL, NULL, NULL, NULL);

// create the compute kernelkernel = clCreateKernel(program, "fft1D_1024", NULL);

// set the args valuesclSetKernelArg(kernel, 0, sizeof(cl_mem), (void *)&memobjs[0]);clSetKernelArg(kernel, 1, sizeof(cl_mem), (void *)&memobjs[1]);clSetKernelArg(kernel, 2, sizeof(float)*(local_work_size[0]+1)*16, NULL);clSetKernelArg(kernel, 3, sizeof(float)*(local_work_size[0]+1)*16, NULL);

// create N-D range object with work-item dimensions and execute kernelglobal_work_size[0] = num_entries;local_work_size[0] = 64;clEnqueueNDRangeKernel(queue, kernel, 1, NULL, global_work_size, local_work_size, 0, NULL, NULL);</source>

The actual calculation: (Based on Fitting FFT onto the G80 Architecture)^[25]<source lang="c">// This kernel computes FFT of length 1024. The 1024 length FFT is decomposed into // calls to a radix 16 function, another radix 16 function and then a radix 4 function

__kernel void fft1D_1024 (__global float2 *in, __global float2 *out,

                         __local float *sMemx, __local float *sMemy) {  int tid = get_local_id(0);  int blockIdx = get_group_id(0) * 1024 + tid;  float2 data[16];

 // starting index of data to/from global memory  in = in + blockIdx;  out = out + blockIdx;  globalLoads(data, in, 64); // coalesced global reads  fftRadix16Pass(data);      // in-place radix-16 pass  twiddleFactorMul(data, tid, 1024, 0);

 // local shuffle using local memory  localShuffle(data, sMemx, sMemy, tid, (((tid & 15) * 65) + (tid >> 4)));  fftRadix16Pass(data);               // in-place radix-16 pass  twiddleFactorMul(data, tid, 64, 4); // twiddle factor multiplication  localShuffle(data, sMemx, sMemy, tid, (((tid >> 4) * 64) + (tid & 15)));  // four radix-4 function calls  fftRadix4Pass(data);      // radix-4 function number 1 fftRadix4Pass(data + 4);  // radix-4 function number 2 fftRadix4Pass(data + 8);  // radix-4 function number 3 fftRadix4Pass(data + 12); // radix-4 function number 4

 // coalesced global writes  globalStores(data, out, 64);

}</source>A full, open source implementation of an OpenCL FFT can be found on Apple's website^[26]

See also

• GPGPU
• CUDA
• DirectCompute
• FireStream
• Larrabee
• Close to Metal
• BrookGPU
• Lib Sh

References

External links

• Official site
• OpenCL for NVIDIA (Download page)
• OpenCL for AMD (Download page)
• OpenCL for IBM Cell broadband Engine (download page)
• OpenCL for S3 Chrome announcement
• OpenCL-Z
• PyOpenCL by Goncalo Carvalho
• PyOpenCL by Andreas Klöckner
• The Open Toolkit library cross-platform C# OpenGL, OpenAL and OpenCL wrapper for Mono/.Net
• GPU Modeling and Development in OpenCL
• First public demonstration of OpenCL by NVIDIA on December 12, 2008 at Siggraph Asia
• First public demonstration of OpenCL by AMD on December 12, 2008 at Siggraph Asia
• OpenCL: What you need to know – article published in Macworld, August 2008
• HPCWire: OpenCL on the Fast Track
• OpenCL Computing
• OpenCL explained as part of a larger article on Snow Leopard (MacOS X 10.6), published at ArsTechnica in August 2009.