Onesweep: A Faster Least Significant Digit Radix Sort for GPUs
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Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 3 Jun 2022.
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Citing papers per year: 2023: 1; 2024: 1; 2025: 2; 2026: 1.
5 papers.
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- 2026AdaGScale: Viewpoint-Adaptive Gaussian Scaling in 3D Gaussian Splatting to Reduce Gaussian-Tile Pairs21 Apr 2026
- 2025Spira: Exploiting Voxel Data Structural Properties for Efficient Sparse Convolution in Point Cloud Networks25 Nov 2025
- 2025A Fast Parallel Median Filtering Algorithm Using Hierarchical Tiling26 Jul 2025
- 2024Multi-Layer Gaussian Splatting for Immersive Anatomy Visualization22 Oct 2024
- 2023Compressed 3D Gaussian Splatting for Accelerated Novel View Synthesis17 Nov 2023