![]() CUDA performance boostĬUDA has improved and broadened its scope over the years, more or less in lockstep with improved NVIDIA GPUs. While OpenCL sounds attractive because of its generality, it hasn’t performed as well as CUDA on NVIDIA GPUs, and many deep learning frameworks either don’t support OpenCL or only support it as an afterthought once their CUDA support has been released. CUDAĬUDA competitor OpenCL was launched in 2009, in an attempt to provide a standard for heterogeneous computing that was not limited to Intel/AMD CPUs with NVIDIA GPUs. Buck later joined NVIDIA and led the launch of CUDA in 2006, the first commercial solution for general purpose computing on GPUs. In 2003, a team of researchers led by Ian Buck unveiled Brook, the first widely adopted programming model to extend C with data-parallel constructs. It wasn’t until later that people used GPUs for math, science, and engineering. At the time, the principal reason for having a GPU was for gaming. By 1996, you could buy a 3D graphics accelerator from 3dfx so that you could run the first-person shooter game Quake at full speed.Īlso in 1996, NVIDIA started trying to compete in the 3D accelerator market with weak products, but learned as it went, and in 1999 introduced the successful GeForce 256, the first graphics card to be called a GPU. ![]() By 1988, you could get a 16-bit 2D VGA Wonder card from ATI (the company eventually acquired by AMD). ![]() Graphics cards are arguably as old as the PC-that is, if you consider the 1981 IBM Monochrome Display Adapter a graphics card. While there have been other proposed APIs for GPUs, such as OpenCL, and there are competitive GPUs from other companies, such as AMD, the combination of CUDA and NVIDIA GPUs dominates several application areas, including deep learning, and is a foundation for some of the fastest computers in the world. CUDA enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation. CUDA is a parallel computing platform and programming model developed by NVIDIA for general computing on its own GPUs (graphics processing units).
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