From InfoWorld: Right now, the market for GPUs for use in machine learning is essentially a market of one: Nvidia.
AMD, the only other major discrete GPU vendor of consequence, holds around 30 percent of the market for total GPU sales compared to Nvidia’s 70 percent. For machine-learning work, though, Nvidia’s lead is near-total. Not just because all the major clouds with GPU support are overwhelmingly Nvidia-powered, but because the GPU middleware used in machine learning is by and large Nvidia’s own CUDA.
AMD has long had plans to fight back. It’s been prepping hardware that can compete with Nividia on performance and price, but it’s also ginning up a platform for vendor-neutral GPU programming resources — a way for developers to freely choose AMD when putting together a GPU-powered solution without worrying about software support.
AMD recently announced its next steps toward those goals. First is a new GPU product, the Radeon Vega, based on a new though previously unveiled GPU architecture. Second is a revised release of the open source software platform, ROCm, a software layer that allows machine-learning frameworks and other applications to leverage multiple GPUs.
Both pieces, the hardware and the software, matter equally. Both need to be in place for AMD to fight back.
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