perf-optimize

perf-optimize is an MLOps & model serving skill for AI agents, published by NVIDIA in the TensorRT-LLM repository on GitHub. Skillspace rates perf-optimize C (72/100) and it passed the safety scan; the rating is based on static analysis only.

Launch and operate this repo's perf-optimize workflow, which iteratively APPLIES TensorRT-LLM serving optimizations — baseline benchmark at one concurrency or a Pareto curve of them (tok/s/user vs tok/s/gpu), analytical SOL projection on by default (via the internal-perf-sol-analysis skill) sizing the headroom the campaign chases, profile-ranked roadmap.yaml (nsys + ncu per-kernel analysis via the perf-nsight-compute-analysis skill), a fixed budget of rounds applying items one at a time gated on measured gain (curve mode uses a Pareto gate; the evaluator accepts, rejects, or pushes back each attempt and nsys-profiles every accept), one final-verification QA benchmark, expected-vs-measured report with Pareto improvement results. Use when the user wants to optimize / improve / speed up a trtllm-serve deployment (throughput, TTFT, TPOT, ITL, e2e latency) or says "run perf-optimize". For diagnosis WITHOUT applying changes, use the perf-analyze workflow instead.

Grade

C

Quality

72 / 100

Safety

Passed

GitHub stars

14,613

Unproven: rated by static analysis only, not yet compared head-to-head.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

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