SATURDAY, OCTOBER 10, 2026|No. 18194
Technology · Programming

Rust Compiler Framework Enables Safe and Efficient GPU Offloading

A new framework integrated into the Rust compiler (rustc) and LLVM backends allows for efficient and memory-safe GPU programming across multiple vendors, achieving performance competitive with native C++ solutions.

Abstract representation of code executing on a GPU.
Abstract representation of code executing on a GPU. · Photo by Nat on Unsplash
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GPU Offload in Rust: Portable, Safe, and Fast

Authors: Manuel S. Drehwald, Marcelo Domínguez, Kevin Sala, Alán Aspuru-Guzik, Johannes Doerfert

High-performance GPU programming has traditionally forced a compromise between execution efficiency and memory safety. While Rust guarantees compile-time memory safety for host CPUs via its strict ownership model, applying these constraints to massively parallel GPU execution environments has previously mandated either vendor-locked Domain-Specific Languages (DSLs) or escaping to explicit unsafe raw pointers. This paper presents a zero-overhead, multi-vendor GPU compilation framework built natively into the Rust compiler (rustc) and LLVM backends.

We leverage Rust's rich type system, ownership system, and strict aliasing guarantees (noalias) to efficiently manage and optimize data transfers through LLVM's Offload infrastructure. We expose the technical challenges of cross-vendor ABI lowering mismatches between Host and Device targets and introduce a two-pass compilation pipeline capable of safely handling both manual and compiler-generated memory movements. Evaluating our framework on RAJAPerf demonstrates that our rustc-based solution can generate competitive LLVM IR for GPU kernels, achieving a solid kernel performance against native, hand-optimized CUDA and HIP C++ baselines.

Comments: 13 pages, 5 figures Subjects: Programming Languages (cs.PL)

PAN's pipeline reviewed approximately 1 open sources for this article. No human editor reviewed this article before publication.

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