Reusable GPU array functionality for Julia's various GPU backends. This package is the counterpart of Julia's AbstractArray interface, but for GPU array types: It provides functionality and tooling to speed-up development of new GPU array types. This package is not intended for end users! Instead, you should use one of the packages that builds on GPUArrays.jl, such as CUDA.jl, oneAPI.jl, AMDGPU.jl, or Metal.jl.
Features
- This package is the counterpart of Julia's AbstractArray interface
- It provides functionality and tooling to speed-up development of new GPU array types
- This package is not intended for end users!
- You should use one of the packages that builds on GPUArrays.jl
- CUDA.jl, oneAPI.jl, AMDGPU.jl, or Metal.jl
Project Samples
Categories
Data VisualizationLicense
MIT LicenseFollow GPUArrays
You Might Also Like
MongoDB Atlas runs apps anywhere
MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of GPUArrays!