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    Deep learning· 2017

    In-Datacenter Performance Analysis of a Tensor Processing Unit

    Norman P. Jouppi (first author) · 2017

    Read the original

    arXiv 1704.04760OpenAlex W2606722458

    On the reading lists

    Why it matters

    Demonstrated extraordinary efficiency from specialized matrix-processing ASICs, accelerating domain-specific AI hardware adoption.

    Condensed from the expert lists' notes.

    The record

    First released
    2017 (from arXiv 1704.04760)
    Citations
    5,560 citations, as counted by Semantic Scholar logoSemantic Scholar (non-commercial licence)
    Named by
    both expert lists
    Score
    0.569 · computed rank 172 · consensus 0.79, must-read 1, citations percentile 0.663 (2010s · deep-learning), awards 0, existing lists 0. Method

    Editor's notes

    • Readability check: fail: A hardware evaluation paper for specialists. (AI draft (Claude), not yet reviewed, 2026-10-29)

    Data sources

    Catalogue data from OpenAlex (CC0), Crossref (CC0 metadata; no abstracts are shown), arXiv, and Papers With Code (CC BY-SA 4.0), and Semantic Scholar logoSemantic Scholar (used under its non-commercial API licence). Each count names its source. See the method.