capture-nsys-profile

Capture Nsight Systems traces for PithTrain runs across parallelism configurations.

327|31|Updated Mar 21, 2026
One-click install
npx skills add https://github.com/mlc-ai/pith-train --skill capture-nsys-profile
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: capture-nsys-profile
Source: https://github.com/mlc-ai/pith-train/tree/main/.agents/skills/capture-nsys-profile
Command: npx skills add https://github.com/mlc-ai/pith-train --skill capture-nsys-profile

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires nsight-systems, pithtrain, and includes scripts (resource) components.

What problem does it solve?

Capture Nsight Systems traces to diagnose performance bottlenecks in MoE training runs using PithTrain, enabling targeted optimization across parallelism configurations.

Core Features & Use Cases

  • Generates per-node .nsys-rep traces for profiling across pipeline, expert, and context parallelism settings.
  • Automatically sizes global batch and run warmup + profiled steps from a released checkpoint to produce representative traces.
  • Integrates with existing checkpoint workflows to produce actionable performance data for kernel timelines and all-to-all overhead analysis.

Quick Start

Run the profile-capture flow with your target model and parallelism configuration to create an .nsys-rep under workspace/capture-nsys-profile.

Frequently Asked Questions about capture-nsys-profile

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I capture Nsight Systems traces for MoE training to analyze performance bottlenecks?

You can capture Nsight Systems traces by running a short PithTrain profile from a released checkpoint. The process automatically sizes the global batch to steady-state and collects representative .nsys-rep files to analyze kernel timelines and all-to-all overhead.

What prerequisites are needed to profile PithTrain runs with Nsight Systems?

Profiling PithTrain with Nsight Systems requires the Nsight Systems CLI on all nodes and a GPU-enabled environment where world_size >= PP*CP*EP. You must also provide a released checkpoint with benchmark inputs prepared by the setup-benchmark-inputs skill.

Can I profile performance across different parallelism configurations like PP, EP, and CP?

Yes, you can profile across adaptive pipeline (PP), expert (EP), and context (CP) parallelism configurations. The profile capture adjusts the global batch to steady-state while collecting representative .nsys-rep traces for each parallelism setting.

How does generating .nsys-rep traces help diagnose GPU training bottlenecks?

Generating .nsys-rep traces provides actionable performance data for kernel timelines and all-to-all communication overhead. This allows you to pinpoint parallelism inefficiencies and apply targeted optimizations across your MoE training configurations.

What is the best way to analyze all-to-all overhead in MoE training workloads?

The best way to analyze all-to-all overhead is to capture Nsight Systems traces during a short PithTrain run. This generates detailed .nsys-rep profiles from a steady-state checkpoint, exposing kernel timelines and communication bottlenecks for optimization.