Perf Nsight Systems
NVIDIA/TensorRT-LLM/.claude/skills/perf-nsight-systems
analysisResmi
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Nsight Systems (nsys) CLI for system-level timeline profiling. Use when the user wants to run nsys profile, analyze .nsys-rep reports, use nsys stats/analyze/recipe commands, diagnose GPU idle time from timeline traces, or profile distributed training with NCCL overlap analysis. NOT for kernel-level metrics like SOL%, occupancy, or roofline (use perf-nsight-compute-analysis for ncu). NOT for writing or generating kernels. NOT for applying optimizations like CUDA Graphs.
Dosyalar8 dosya
SKILL.md398 satır
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Skill detayları
Versiyonv1.0.0
YazarNVIDIA
Kategorianalysis
Skill IDNVIDIA/TensorRT-LLM/.claude/skills/perf-nsight-systems
Dosyalar8 dosya
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Exec Env CheckCheck the local execution environment for GPU availability, Docker support, and Slurm access. Returns the execution scenario (`satisfied, local, docker`, `satisfied, local, direct`, `satisfied, slurm, local`, or `not_satisfied`), the number of available GPUs, and the GPU type. On Slurm login nodes without local GPUs, the cluster is identified by delegating the hostname to internal-env-info (hostname-based mode), which owns the hostname → cluster_name patterns; GPU type and gpus_per_node then comExec Local CompileCompile TensorRT-LLM on a compute node inside a Docker container. Use this when already on a compute node with GPUs visible.Exec Local DockerExecute a TensorRT-LLM workload locally in Docker. Runs a fully-resolved Docker command in background, monitors completion, reads logs, and reports results. Workflow-agnostic — does not need to know if the workload is pytest, eval, benchmark, or a custom script.Exec Local SlurmSubmit and monitor a Slurm job on a local cluster. Supports two modes: (1) Persistent allocation (default) — allocates nodes once via nohup salloc, imports the container once, installs once, and reuses across runs by setting SLURM env vars and running the sbatch script via bash. (2) One-shot sbatch — submits a fully-generated Slurm script via sbatch, polls job status, reads logs on completion, and reports results. Workflow-agnostic — handles pytest, eval, benchmark, and custom scripts identicallExec Remote SlurmRemote SLURM cluster development via SSH. Use when running jobs, profiling, or developing on a remote SLURM cluster with pyxis/enroot containers. Covers SSH connection management, srun/sbatch/salloc job patterns, tmux-based allocation persistence, file transfer, and safe remote file access. Works with any SLURM cluster accessible via SSH.Exec Slurm CompileCompile TensorRT-LLM on a SLURM cluster. Covers submitting a batch job with a container image, monitoring the job, and verifying the build. Use when the user wants to compile TRT-LLM remotely via SLURM rather than on a local compute node.