cuda-oxide is an experimental Rust-to-CUDA compiler that lets you write (SIMT) GPU kernels in safe(ish), idiomatic Rust. It compiles standard Rust code directly to PTX — no DSLs, no foreign language bindings, just Rust.
A curated list of awesome parallel computing resources
📚 计算机体系结构与C++书籍收集(持续更新)
Compare and test GPU programming frameworks / Comparaison d'outils pour GPU
CHARM: Composing Heterogeneous Accelerators on Heterogeneous SoC Architecture
A mixed-criticality platform built around Cheshire, with a number of safety/security and predictability features. Ready-to-use FPGA flow on multiple boards is available.
Heterogeneous Research Platform (HERO) for exploration of heterogeneous computers consisting of programmable many-core accelerators and an application-class host CPU, including full-stack software and hardware.
Concurrent CPU-GPU Programming using Task Models
Monte Carlo eXtreme for OpenCL (MCXCL)
a unified cross-architecture heterogeneous CFD solver
Data Parallel Extensions for Python*
"Optimizing Performance and Energy Efficiency in Massively Parallel Systems" PhD Dissertation repository.
AIM: Accelerating Arbitrary-precision Integer Multiplication on Heterogeneous Reconfigurable Computing Platform Versal ACAP (Full Paper accepted to ICCAD2023)!
A Python based programming system for heterogeneous computing
[ICLR 2024] FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler
🧠 One LLM, split across a Mac (Apple MPS) + a Windows PC (NVIDIA CUDA) — heterogeneous pipeline inference over a framework-neutral wire, bit-for-bit identical to single-machine. No torch.distributed, no datacenter.
⚡ Real-time dual-GPU OpenCL risk engine — enumerate 3.6M lottery draw permutations & compute per-outcome P&L in ~3s on 2× RTX 2080. Hand-rolled C99 kernels, multi-GPU divide-and-conquer, production-grade. 🎲🚀
Usability and Performance in Heterogeneous Computing. Official EngineCL repository. Peer-reviewed (FGCS).
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