chelsea0x3b/cudarc

Health v2 · maintenance only

Adoption not part of the score

1213 stars · 166 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

cudarc is a safe, minimal Rust wrapper around the NVIDIA CUDA toolkit, exposing the CUDA driver API plus libraries such as NVRTC, cuBLAS/cuBLASLt, cuDNN, cuRAND, NCCL, cuSPARSE, cuSOLVER, cuFFT, cuFILE, and CUPTI. It supports dynamic loading (no build-time CUDA required), dynamic linking, and static linking, with cargo feature flags to select CUDA 11.4-13.3, cuDNN 8.9-9.21, and NCCL 2.22-2.30 versions.

Use cases

• run custom CUDA kernels from Rust
• call cuBLAS or cuDNN from a Rust program
• safely allocate and transfer GPU memory in Rust
• compile CUDA kernels at runtime with NVRTC
• do multi-GPU communication with NCCL in Rust
• GPU-accelerate a Rust application on NVIDIA hardware
• use CUDA without a CUDA toolkit installed at build time
• write deep learning primitives in Rust on top of cuDNN

When to choose

• you are writing Rust that needs NVIDIA GPU acceleration
• you want safe, idiomatic handling of CUDA contexts, streams, and device memory
• you need FFI bindings to cuBLAS, cuDNN, cuRAND, or NCCL without writing unsafe C interop yourself
• you want to build without a local CUDA toolkit via the dynamic-loading feature
• you need to pin bindings to a specific CUDA, cuDNN, or NCCL version

When to avoid

• you target AMD or Intel GPUs rather than NVIDIA CUDA
• you want a high-level tensor library with autodiff rather than raw CUDA bindings
• you are not working in Rust
• you need exhaustive coverage of every CUDA API, since cudarc intentionally exposes a minimal subset

Facets

library · maturity active

gpu-computing gpu-computing machine-learning developer-tools rust windows cuda cuda-bindings nvidia cublas cudnn nccl nvrtc curand cusparse cufft cupti ffi-bindings safe-rust gpgpu multi-gpu dynamic-loading gpu linux

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