This is a news story, published by IEEE Spectrum, that relates primarily to Moore news.
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benchmark effortIEEE Spectrum
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87% Informative
AI training on new suite of benchmarks is improving at about twice the rate one would expect from Moore ’s Law.
The benchmark tests, called MLPerf v4.1 , consist of six tasks: recommendation, the pre-training of the large language models (LLM) GPT-3 and BERT -large, the fine tuning of the Llama 2 70B large language model, object detection, graph node classification, and image generation.
MLPerf is only beginning to measure the power of training neural networks.
Dell Technologies was the sole entrant in the energy category, with an eight -server system containing 64 Nvidia H100 GPUs and 16 Intel Xeon Platinum CPUs.
The only measurement made was in the LLM fine-tuning task (Llama2 70B) The result does potentially provide a ballpark for power consumption of similar systems.
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