The NVIDIA CUDA-X math libraries empower developers to build accelerated applications for AI, scientific computing, data processing, and more. Two of the most important applications of CUDA-X libraries are training and inference LLMs, whether for use in everyday consumer applications or highly specialized scientific domains like drug discovery. Multiple CUDA-X libraries are indispensable…
]]>The NVIDIA H100 Tensor Core GPU, based on the NVIDIA Hopper architecture with the fourth generation of NVIDIA Tensor Cores, recently debuted delivering unprecedented performance and sweeping AI benchmarks such as MLPerf training. A significant fraction of operations in AI and machine learning benchmarks are general matrix multiplications (GEMMS), which are also referred to as matmul…
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