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The lesson on NVIDIA terminology continues, here are the ins and outs on OpenCL


OpenCL (Open Computing Language) is a new heterogeneous computing environment, that runs on the CUDA architecture. It will allow developers to harness the massive parallel computing power of NVIDIA GPU’s to create compelling computing applications.

In partnership with NVIDIA, OpenCL was submitted to Khronos by Apple in the summer of 2008 with the goal of forging a cross platform environment for GPU computing. NVIDIA chairs the OpenCL working group with direct support from NVIDIA’s SW engineering team. The SIGGRAPH ASIA Khronos OpenCL presentation by Neil Trevett of NVIDIA can be found here.

As part of the OpenCL presentation NVIDIA featured the world's first OpenCL GPU demonstration, running on a laptop NVIDIA GPU.

Go here to download OpenCL: http://developer.nvidia.com/object/opencl.html

As a processor company, NVIDIA enthusiastically supports all languages and API’s that enable developers to access the parallel processing power of the GPU. In addition to OpenCL and NVIDIA’s CUDA C extensions, there are other programming models available: Last fall Microsoft provided a compute shader model in their latest DirectX Software Development Kit. Besides these GPU computing offerings there is also a Fortran language solution recently available in early access from The Portland Group.

NVIDIA has a long history of embracing and supporting standards since a wider choice of languages improve the number and scope of applications that can exploit parallel computing on the GPU. With C and Fortran language support here today and OpenCL and DirectX Compute availability this year, GPU computing is now mainstream. NVIDIA is the only processor company to offer this breadth of open languages for the GPU.

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