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NVIDIA says its GPUs are in fact programmable in C language

Yesterday, DailyTech ran a story about details on Intel's upcoming Larrabee architecture for the graphics market. One of Intel's most important talking points when it plays up the benefits of Larrabee over NVIDIA's GPUs is the fact that NVIDIA's GPUs require developers to learn a new programming language called CUDA.

Intel says that with its Larrabee architecture developers can simply program in C or C++ languages for just as they would for any other x86 processor. According to Intel, the ability to program Larrabee with C or C++ makes it much easier for developers to port applications from other platforms to the Larrabee architecture.

After DailyTech ran the story, NVIDIA wanted to address what it considers to be misinformation when it comes to CUDA. NVIDIA says:

CUDA is a C-language compiler that is based on the PathScale C compiler. This open source compiler was originally developed for the x86 architecture. The NVIDIA computing architecture was specifically designed to support the C language - like any other processor architecture. Competitive comments that the GPU is only partially programmable are incorrect - all the processors in the NVIDIA GPU are programmable in the C language.

NVIDIA's approach to parallel computing has already proven to scale from 8 to 240 GPU cores. Also, NVIDIA is just about to release a multi-core CPU version of the CUDA compiler. This allows the developer to write an application once and run across multiple platforms. Larrabee's development environment is proprietary to Intel and, at least disclosed in marketing materials to date, is different than a multi-core CPU software environment.

Andrew Humber from NVIDIA distilled things a bit further saying, "CUDA is just our brand name for the C-compiler. They aren't two different things."

Humber also pointed out that at NVIDIA's financial analyst day in April it showed an astrophysics simulation running on integrated graphics with an eight-core GPU, a GeForce 8 series GPU with 128 cores and a quad-core CPU. NVIDIA says that the demonstration used exactly the same binary program across the range of GPUs and the exact same source code for the CPU and GPU.





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