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A simple library-less CUDA implementation of the OneSweep sorting algorithm.

License: MIT License

Cuda 100.00%
cuda gpgpu onesweep parallel-programming parallel-sorting sorting-algorithms

onesweep's Introduction

Notice: This repository has been archived.

This repository has been archived. The development and maintenance of its contents has been moved to https://github.com/b0nes164/GPUSorting.

OneSweep

A simple library-less CUDA implementation of the Adinets and Merrill's OneSweep sorting algorithm. Given $2^{28}$ uniform random 32-bit keys, our implementation achieves a performance of $\sim$ 10.9 G keys/sec on a 2080 super, which is identical to the performance achieved with the CUB library.

The purpose of this repo is to demystify the implmentation of the algorithm. It is not intended for production or use, instead a proper implementation can be found at the CUB library. Notably our implementation lacks: short circuit evaluation, support for data types besides unsigned int, support for aligned scattering, and tuning for cards other than the 2080 super. If you would like to run this code yourself, simply grab the latest version of the CUDA toolkit.

Strongly Suggested Reading / Bibliography

Andy Adinets and Duane Merrill. Onesweep: A Faster Least Significant Digit Radix Sort for GPUs. 2022. arXiv: 2206.01784 [cs.DC]

Duane Merrill and Michael Garland. “Single-pass Parallel Prefix Scan with De-coupled Lookback”. In: 2016. url: https://research.nvidia.com/publication/2016-03_single-pass-parallel-prefix-scan-decoupled-look-back

Saman Ashkiani et al. “GPU Multisplit”. In: SIGPLAN Not. 51.8 (Feb. 2016). issn: 0362-1340. doi: 10.1145/3016078.2851169. url: https://doi.org/10.1145/3016078.2851169.

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