High-performance GPU programming in a high-level language. JuliaGPU is a GitHub organization created to unify the many packages for programming GPUs in Julia. With its high-level syntax and flexible compiler, Julia is well-positioned to productively program hardware accelerators like GPUs without sacrificing performance. The latest development version of CUDA.jl requires Julia 1.8 or higher. If you are using an older version of Julia, you need to use a previous version of CUDA.jl. This will happen automatically when you install the package using Julia's package manager.
Features
- CUDA.jl v4.4 will be the last version with support for CUDA 11.0-11.3 (deprecated in v5.0)
- CUDA.jl features a user-friendly array abstraction, making it easier to work with NVIDIA CUDA GPUs using the Julia programming language
- The package provides a compiler for writing CUDA kernels in Julia, enabling developers to write GPU-specific code within the Julia environment
- CUDA.jl offers wrappers for various CUDA libraries, simplifying the integration of existing CUDA functionality into Julia applications
- The latest development version of CUDA.jl requires Julia 1.8 or higher, ensuring compatibility with the latest versions of the Julia programming language
- To use CUDA.jl, a CUDA-capable GPU with compute capability 3.5 (Kepler) or higher is required, along with an NVIDIA driver that supports CUDA 11.0 or newer
Project Samples
Categories
Data VisualizationLicense
MIT LicenseFollow CUDA.jl
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