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Ferjaoui
d3a5f842bf
throughput.py measures wall-clock FPS without nsys, for the copy-out (find_clusters_batched) and zero-copy (BatchView) paths, at 3x3 to 9x9 and 1 and 4 streams. On the A100, zero-copy with 4 streams reaches 94-102 % of the bound predicted by the nsys probes.
GPU performance probes
Nsight Systems probes for the CUDA classes: per-engine GPU time per frame
(kernel, H2D, D2H), duty cycles and the roofline. One folder per class, each
with its own driver, traced process, README and results/:
| folder | class |
|---|---|
cf/ |
ClusterFinderCUDA |
Shared by all of them:
| file | role |
|---|---|
common.py |
paths (AARE_REPO, AARE_BUILD, AARE_PERF_DATA, NSYS), guards (fresh build, idle GPU), env.json stamp, results folder |
gpu_span.py |
reads an nsys SQLite export: busy time, duty cycle and roofline per engine, optionally for one kernel name only |
Requirements (a CUDA build of the Python extension, Nsight Systems, the dataset, an idle GPU) are listed in each folder's README.