← GPU latency results

gpu/routine_workflow

profile: nvidia-gpuno machine-readable summary

Legacy report: ingestion provenance is unrecorded; no raw artifact is inferred.

Original report

GPU routine command wall

Raw selection: /home/shinaoka/tensor4all/tenferro-benchmark/.worktrees/gpu-refresh-20261017/data/results/nvidia-gpu/gpu/routine_selection/20261016_234450.

tenferro-rs 2754c8c85dcc35c1b63cb7bbdd94ddfd7ea5746e; harness f94171e1f76a246bdaee4f2e008ffc74149a6d5f. GPU: NVIDIA A100 80GB PCIe (GPU-530977e1-4968-9283-4129-9fbec3e66542).

Coverage quick, effort standard; core measured 27/27. Routine controls selected: True.

Controls measured 10/10; state observations 8/8. Untimed states are not operation timings.

Command checkpoint/phase Seconds
Core through final suite report 276.424
Remaining controls/accounting/reporting 108.017
Script through final wall checkpoint 384.442

Scope: script clock read through core and control collection, validation, accounting and report writes; excludes devcontainer CLI startup and final wall metadata/report formatting.

Reference budget: 300 seconds for NVIDIA GeForce RTX 3060, quick/standard. Conditions: existing CUDA devcontainer and dependency cache; mandatory Rust binary rebuilds included.

Budget scope: core and routine controls through accounting/reporting; devcontainer CLI startup and final wall metadata/report formatting excluded. Reference characterization: data/results/nvidia-gpu/gpu/routine_selection/20261013_234113.

Observation: budget not evaluated for this hardware, selection or incomplete/unmeasured run.

Budget status is descriptive and never changes functional success. A cold dependency build or busy host can exceed it; retain the observation rather than treating it as a confirmed regression. Detailed core case phases and control observations are published separately for the same coverage profile and raw-run identity. These observations establish no implementation speedup.