Ten Lessons From Three Generations Shaped Google’s TPUv4i : Industrial Product

2021 ACM/IEEE 48th Annual International Symposium on Computer Architecture (ISCA)(2021)

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摘要
Google deployed several TPU generations since 2015, teaching us lessons that changed our views: semi-conductor technology advances unequally; compiler compatibility trumps binary compatibility, especially for VLIW domain-specific architectures (DSA); target total cost of ownership vs initial cost; support multi-tenancy; deep neural networks (DNN) grow 1.5X annually; DNN advances evolve workloads; some inference tasks require floating point; inference DSAs need air-cooling; apps limit latency, not batch size; and backwards ML compatibility helps deploy DNNs quickly. These lessons molded TPUv4i, an inference DSA deployed since 2020.
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关键词
TPUv4i,backwards ML compatibility,inference DSA,inference tasks,DNN advances,deep neural networks,support multitenancy,initial cost,VLIW domain-specific architectures,binary compatibility,compiler compatibility,semiconductor technology advances,TPU generations,industrial product,Google
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