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Alibaba's aegaeon system reduces nvidia gpu usage by 82% for serving multiple large language models, cutting required gpus from 1,192 to 213 while boosting output by 9x and slashing latency by 97% Alibaba cloud details a gpu pooling system that it claims reduced the number of nvidia h20 required by 82% when serving dozens of llms of up to 72b parameters — the new aegaeon system can serve dozens of large language models using a fraction of the gpus previously required, potentially reshaping ai workloads more Amid us export curbs, this innovation enhances ai efficiency and scalability for cloud providers.
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Alibaba group holding has introduced a computing pooling solution that it said led to an 82 per cent cut in the number of nvidia graphics processing units (gpus) needed to serve its artificial. Alibaba introduces aegaeon, a computing pooling system reducing nvidia gpu reliance by 82%. According to a report from south china morning post, aegaeon allows a single gpu to serve multiple ai models at once, drastically reducing the total hardware needed
In testing, the system cut the number of nvidia h20 gpus required to serve dozens of models — some with up to 72 billion parameters — from 1,192 to just 213.
