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Onesweep: A Faster Least Significant Digit Radix Sort for GPUs

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arxiv 2206.01784 v1 pith:G7QN6AE4 submitted 2022-06-03 cs.DC cs.DS

classification cs.DCcs.DS
keywords radixsortingapproachdigitglobalmemorysortalgorithm
verification ladder T0 review T1 audit T2 compute T3 formal
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We present Onesweep, a least-significant digit (LSD) radix sorting algorithm for large GPU sorting problems residing in global memory. Our parallel algorithm employs a method of single-pass prefix sum that only requires ~2n global read/write operations for each digit-binning iteration. This exhibits a significant reduction in last-level memory traffic versus contemporary GPU radix sorting implementations, where each iteration of digit binning requires two passes through the dataset totaling ~3n global memory operations. On the NVIDIA A100 GPU, our approach achieves 29.4 GKey/s when sorting 256M random 32-bit keys. Compared to CUB, the current state-of-the-art GPU LSD radix sort, our approach provides a speedup of ~1.5x. For 32-bit keys with varied distributions, our approach provides more consistent performance compared to HRS, the current state-of-the-art GPU MSD radix sort, and outperforms it in almost all cases.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Efficient Differentiable Hardware Rasterization for 3D Gaussian Splatting

    cs.GR 2025-05 conditional novelty 7.0 of 10

    A hardware-rasterization pipeline with programmable blending and subgroup/quad gradient reduction achieves 3.07x end-to-end speedup and a 37x sorting-memory cut for 3D Gaussian Splatting.

  2. Vortex: Overcoming Memory Capacity Limitations in GPU-Accelerated Large-Scale Data Analytics

    cs.DB 2025-02 conditional novelty 7.0 of 10

    By routing data through idle IO paths of neighboring GPUs, Vortex lets a single GPU run analytics on datasets exceeding its memory at 140GB/s aggregate transfer and beats CPU baselines.

  3. A Fast Parallel Median Filtering Algorithm Using Hierarchical Tiling

    cs.DC 2025-07 conditional novelty 6.0 of 10

    Hierarchical tiling lets sorting-based median filters on GPUs reach O(k log k) and O(k) per-pixel complexity for k x k kernels, with large measured speedups.

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