claude

tpu-perf

Systematic analysis of TPU pretraining efficiency. profile-anatomy: schema + reference scripts for xplane.pb / trace.json.gz. comm-analysis: per-axis NCCL bus BW, peak ICI utilization, and per-step compute/comm overlap. compute-breakdown: source-line aggregation, layer scoping, non-compute audit, v7x roofline shortfall. memory-profile: HBM peak occupancy, alive-buffer attribution, lifetime/shape/tf_op/parent_jit rollups.

0 on GitHubv0.3.0Apache-2.0updated 1 month agoperformance
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Plugin tpu-perf from marketplace primatrix-skills in primatrix/skills. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (4)

  • comm-analysis

    Use when analyzing communication on a TPU pretraining profile — extracts every comm primitive (async + sync, TC + SparseCore), attributes axes via HLO replica_groups, computes per-row NCCL bus BW vs per-axis peak ICI BW (peak_link × k_torus_dims × directions_per_dim; TPUv7x: 200 GB/s bidir per link

  • compute-breakdown

    Use when analyzing TPU pretraining compute efficiency from xplane.pb — produces source-line-aggregated HLO duration tables, layer-scoped breakdowns, non-compute (padding/cast/copy) audits, and v7x roofline shortfall vs theoretical peak. Reads schema documented by profile-anatomy.

  • memory-profile

    Use when analyzing TPU pretraining HBM occupancy from a profile directory — locates the static HBM peak (the same number TensorBoard's Memory Viewer shows), enumerates every buffer alive at the peak schedule moment with size / HLO instruction / opcode / op_name, and rolls the alive set up by opcode

  • profile-anatomy

    Use when reading TPU pretraining profiles (xplane.pb, trace.json.gz) — describes the on-disk layout, the XSpace/XPlane/XLine/XEvent/XStat hierarchy, and provides reference scripts that future tpu-perf skills can read as schema documentation.

View source on GitHub

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