Show HN: cuTile Rust: Safe, data-race-free GPU kernels in Rust
cuTile Rust ( cutile-rs ) is a tile-based system for writing memory-safe, data-race-free GPU kernels in idiomatic Rust. It extends Rust's ownership discipline across the GPU launch boundary: mutable tensors are partitioned into disjoint pieces before launch, immutable tensors are shared, and generated launchers preserve ownership while GPU work is in flight. The same model supports synchronous launches, asynchronous pipelines, and CUDA graph replay. The #[cutile::module] macro embeds a captured Rust AST for each kernel in the host binary; when a kernel is needed, cuTile Rust JIT-compiles that AST through CUDA Tile IR into a GPU cubin. Local opt-outs remain available when lower-level control is needed.
We are excited to release this research project as a demonstration of how GPU programming can be made available in the Rust ecosystem. The software is in an early stage and under active development: you should expect bugs, incomplete features, and API breakage as we work to improve it. That being said, we hope you'll be interested to try it in your work and help shape its direction by providing feedback on your experience.
Please check out CONTRIBUTING.md if you're interested in contributing.
The #[cutile::module] macro transforms add into a GPU kernel and generates a host-side launcher. The host code constructs lazy tensor operations, partitions the mutable output into 128-element chunks, and calls .sync() to JIT-compile and execute the kernel.
The kernel signature carries the access discipline into device code: z is the exclusive mutable output, while x and y are shared read-only inputs. The body loads input tiles matching the output partition, adds them, and stores the result. The launch grid (8, 1, 1) is inferred from the partition: 1024÷128 = 8 tiles.
The cuTile Rust paper, Fearless Concurrency on the GPU , is available here . On NVIDIA B200, cuTile Rust reaches 7 TB/s for element-wise operations and 2 PFlop/s for GEMM, about 91% of peak memory bandwidth and 92% of dense f16 peak, respectively. The GEMM result is competitive with cuBLAS, and the B200 safety-overhead microbenchmarks show that cuTile Rust adds safety without measurable runtime overhead: safe Rust persistent GEMM reaches 2.07 PFlop/s at M=N=K=8192 (92% of the B200 dense f16 peak), within 0.3% of the corresponding low-level Tile IR variant.