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B200s have an incremental increase in FP64 and FP32 performance over H100s. That is the number format that HPC people care about. The MI300A can get to 150% th
by pclmulqdq 2y ago
B200s have an incremental increase in FP64 and FP32 performance over H100s. That is the number format that HPC people care about.
The MI300A can get to 150% the FP64 peak performance that B200 devices can get, although AMD GPUs have historically underperformed their spec more than Nvidia GPUs. It's possible that B200 devices are actually behind for HPC.
- cayleyh 2y agoTop line comparison numbers for reference: https://www.theregister.com/2024/03/18/nvidia_turns_up_the_ai/ https://www.theregister.com/2024/03/18/nvidia_turns_up_the_a... It does seem like Nvidia is prioritizing int8 / fp8 performance over FP64, which given the current state of the ML marketplace is a great idea.
- nextos 2y agoMI300 also have decent performance in FP16 (~108 TFLOPS). Not as good as NVIDIA, but it's getting there. Anyone has experience using these on JAX? Support is said to be decent, but no idea if it's good enough for research-oriented tasks, i.e. stable enough for training and inference.