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trt-perf-analysis

Official

Analyze and validate TensorRT performance data with precision.

Software Engineering#optimization#performance analysis#tensorrt#backend comparison#layer profiling
AuthorNVIDIA
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill provides a comprehensive analysis and validation of TensorRT performance data, enabling users to understand and optimize their models efficiently.

Core Features & Use Cases

  • Performance Analysis: Validate and analyze TensorRT performance data from paired layer-info JSON and profile/latency JSON files.
  • Model Validation: Verify that layer/profile JSON files are valid and from the same model.
  • Basic Model Information: Infer basic model information from the analysis.
  • Optimization Opportunities: Identify fusion or latency optimization opportunities.
  • Markdown Report: Generate a concise Markdown performance report.
  • JSON Data: Provide structured JSON data for further analysis.
  • Use Case: Use this Skill when you need to inspect TensorRT performance reports, verify data integrity, and identify areas for optimization.

Quick Start

Run the analyze_trt_perf.py script with the input folder path: ./scripts/analyze_trt_perf.py /path/to/input/folder

Dependency Matrix

Required Modules

None required

Components

scriptsreferencesassets

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: trt-perf-analysis
Download link: https://github.com/NVIDIA/TensorRT/archive/main.zip#trt-perf-analysis

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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