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One of the key metrics in determining if the LLM inference server is performant is by looking at the memory bandwidth utilization. This is a function of the throughput and total GPU/accelerator HBM bandwidth. Calculation taken from PyTorch blog post here: https://pytorch.org/blog/accelerating-generative-ai-2/#step-2-alleviating-memory-bandwidth-bottleneck-through-int8-weight-only-quantization-1574-toks
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One of the key metrics in determining if the LLM inference server is performant is by looking at the memory bandwidth utilization. This is a function of the throughput and total GPU/accelerator HBM bandwidth. Calculation taken from PyTorch blog post here: https://pytorch.org/blog/accelerating-generative-ai-2/#step-2-alleviating-memory-bandwidth-bottleneck-through-int8-weight-only-quantization-1574-toks
The text was updated successfully, but these errors were encountered: