CuPy – A NumPy-compatible array library accelerated by CUDA

• Overview
• Installation Guide
  • Requirements
  • Installing CuPy
  • Installing CuPy from conda-forge
  • Installing CuPy from Source
  • Uninstalling CuPy
  • Upgrading CuPy
  • Reinstalling CuPy
  • Using CuPy inside Docker
  • FAQ
• Tutorial
  • Basics of CuPy
  • User-Defined Kernels
• API Reference
  • Multi-Dimensional Array (ndarray)
  • Universal Functions (ufunc)
  • Routines
  • SciPy-compatible Routines
  • Sparse matrices
  • Multi-dimensional image processing
  • NumPy-CuPy Generic Code Support
  • Memory Management
  • Low-Level CUDA Support
  • Kernel binary memoization
  • Custom kernels
  • Automatic Kernel Parameters Optimizations
  • Interoperability
  • Testing Modules
  • Profiling
  • Environment variables
  • Difference between CuPy and NumPy
  • Comparison Table
  • Miscellaneous functions

Development

• API Compatibility Policy
  • Versioning and Backward Compatibilities
  • Processes to Break Backward Compatibilities
  • Supported Backward Compatibility
  • Installation Compatibility
• Contribution Guide
  • Classification of Contributions
  • Development Cycle
  • Issues and Pull Requests
  • Coding Guidelines
  • Unit Testing
  • Documentation
  • Tips for Developers

Misc Notes

• Using CuPy on AMD GPU (experimental)
  • Requirements
  • Building CuPy for ROCm
• Upgrade Guide
  • CuPy v8
  • CuPy v7
  • CuPy v6
  • CuPy v5
  • CuPy v4
  • CuPy v2
• License
  • NumPy
  • SciPy