GPU Profiler

Open-source web-based GPU performance visualization tool that transforms NVIDIA profiling data into interactive insights for CUDA engineers.

Part of the RightNow AI ecosystem. Want 180x more powerful AI assistance for your entire codebase? Try RightNow AI Code Editor.

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Quick Start

# Clone and install
git clone https://github.com/RightNow-AI/gpu-profiler.git
cd gpu-profiler
npm install

# Start development server
npm run dev

# Open http://localhost:3000 and drop your .nvprof files!

Live Demo

Try GPU Profiler - Upload your profiling files instantly

Demo

Features

• Interactive Visualizations - Timeline, flame graphs, and heatmaps powered by D3.js
• Multiple Format Support - .nvprof, .nsys-rep, and .json profiling files
• Real-time Analysis - Client-side processing for instant results
• Bottleneck Detection - AI-powered hints for performance optimization
• Shareable Results - Generate links to share profiling insights
• Export Capabilities - JSON, CSV, and Chrome Tracing format export
• Professional UI - Clean, modern interface with JetBrains typography

How It Works

graph LR
    A[Upload .nvprof/.nsys] --> B[Parse Profile Data]
    B --> C[Generate Visualizations]
    C --> D[Timeline View]
    C --> E[Flame Graph]
    C --> F[Heatmap]
    D --> G[Bottleneck Analysis]
    E --> G
    F --> G
    G --> H[Export & Share]
    
    style A fill:#e1f5fe
    style H fill:#c8e6c9
    style G fill:#fff3e0

Loading

1. Upload - Drop your NVIDIA profiling files (.nvprof, .nsys-rep, .json)
2. Parse - Client-side processing extracts kernel launches and GPU metrics
3. Visualize - Interactive timeline, flame graphs, and utilization heatmaps
4. Analyze - AI-powered bottleneck detection and optimization hints
5. Share - Export results or generate shareable links

Installation

Requirements

• Node.js 18+
• NPM or Yarn
• Modern web browser (Chrome, Firefox, Safari, Edge)

Setup

# Clone repository
git clone https://github.com/RightNow-AI/gpu-profiler.git
cd gpu-profiler

# Install dependencies
npm install

# Start development server
npm run dev

# Build for production
npm run build
npm start

# Verify installation at http://localhost:3000

Architecture

app/
├── components/           # React components
│   ├── visualizations/  # D3.js visualization components
│   ├── file-upload.tsx  # Drag & drop upload
│   └── profiler-interface.tsx
├── lib/
│   ├── parsers/         # File format parsers
│   ├── utils.ts         # Utility functions
│   ├── sharing.ts       # URL sharing logic
│   └── export.ts        # Export functionality
├── store/               # Zustand state management
├── types/               # TypeScript definitions
└── globals.css          # Tailwind + custom styles

Key Technologies

• Next.js 15 - React framework with App Router
• TypeScript - Type safety and developer experience
• D3.js - Data-driven visualizations
• Tailwind CSS - Utility-first styling
• Zustand - Lightweight state management
• Lucide React - Clean, consistent icons

Performance

• Client-side processing - No data leaves your browser
• Efficient parsing - Handles large profiling files (up to 100MB)
• Optimized renders - Smooth interactions even with thousands of kernels
• Memory efficient - Smart data compression for sharing

Privacy & Security

• 100% client-side - Your profiling data never leaves your device
• No tracking - We don't collect any analytics or personal data
• Secure sharing - Shared links use URL-safe encoding
• Open source - Full transparency, audit the code yourself

Contributing

We welcome contributions! Please see our Contributing Guide for details.

Development Workflow

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Make your changes
4. Run tests: npm test
5. Commit: git commit -m 'Add amazing feature'
6. Push: git push origin feature/amazing-feature
7. Open a Pull Request

Reporting Issues

Found a bug or have a feature request? Open an issue with:

• Clear description of the problem
• Steps to reproduce
• Expected vs actual behavior
• Sample profiling file (if applicable)

Roadmap

v1.1 (Next Release)

• Live profiling - Connect to ncu/nsys running locally
• WebGPU support - Chrome WebGPU trace compatibility
• Multi-file comparison - Compare multiple profiling sessions
• Advanced filters - Filter kernels by occupancy, duration, etc.

v1.2 (Future)

• AI optimization - Integration with RightNow AI's CUDA analyzer
• Code mapping - Upload kernel source code for line-by-line analysis
• Collaborative features - Team workspaces and annotations
• API access - Programmatic access for CI/CD integration

Enterprise

Need advanced features for your team? RightNow AI offers:

• Live inline profiling in the AI-powered code editor
• Custom optimization rules for your specific kernels
• Advanced AI analysis with natural language explanations
• Team collaboration features and workspace management

Performance Features

GPU Profiler provides comprehensive performance insights:

Category	Features
Kernel Analysis	Execution time, occupancy, register usage, memory throughput
Memory Profiling	Transfer patterns, bandwidth utilization, cache efficiency
Bottleneck Detection	AI-powered optimization suggestions and performance hints
Visual Analytics	Interactive charts, zoom capabilities, data export

Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

License

MIT License - free for personal, educational, and commercial use.

Links

• Website: www.rightnowai.co
• GPU Profiler: profiler.rightnowai.co
• Documentation: docs.rightnowai.co
• Discord: Join our community
• Twitter/X: @rightnowai_co

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Made with love by the RightNow AI Team