Synthesis of Sorting Kernels

Recently, AlphaDev has shown significant advances in the synthesis of branchless sorting kernels for arrays of lengths 3 to 5. In this paper, we propose an enumerative search technique based on A* search and present novel optimality-pre­serving heuristics and non-optimality-preserving cuts for sorting kernel synthesis. Our algorithm outperforms AlphaDev in synthesis time by two orders of magnitude ran on a standard notebook instead of a TPU cluster. Because our algorithm can explore the solution space, we are able to enumerate all correct sorting kernels for length 3 and simply select the best-performing one. For larger array lengths, we intelligently sample the solution space and find a sorting kernel that outperforms the state-of-the-art. Furthermore, we establish a new tight lower bound for the shortest sorting kernel for length 4. Finally, we provide a comprehensive comparison against several other existing synthesis techniques and show that none of them is able to synthesize sorting kernels for arrays longer than 3.

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Publication Details

Published
2025-02-22
DOI
https://doi.org/10.1145/3696443.3708954
Citations
2
Primary Topic
Machine Learning and Algorithms
Type
article
Field-Weighted Citation Impact
4.96
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article

Synthesis of Sorting Kernels

Sebastian Hack, Marcel Ullrich
2 citations
Machine Learning and Algorithms
4.96
article

Synthesis of Sorting Kernels

Sebastian Hack, Marcel Ullrich
article en
2 citations

Abstract

Recently, AlphaDev has shown significant advances in the synthesis of branchless sorting kernels for arrays of lengths 3 to 5. In this paper, we propose an enumerative search technique based on A* search and present novel optimality-pre­serving heuristics and non-optimality-preserving cuts for sorting kernel synthesis. Our algorithm outperforms AlphaDev in synthesis time by two orders of magnitude ran on a standard notebook instead of a TPU cluster. Because our algorithm can explore the solution space, we are able to enumerate all correct sorting kernels for length 3 and simply select the best-performing one. For larger array lengths, we intelligently sample the solution space and find a sorting kernel that outperforms the state-of-the-art. Furthermore, we establish a new tight lower bound for the shortest sorting kernel for length 4. Finally, we provide a comprehensive comparison against several other existing synthesis techniques and show that none of them is able to synthesize sorting kernels for arrays longer than 3.

Saarland University (DE)
Openalex Percentile: Top 6%
Machine Learning and Algorithms
4.96
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Synthesis of Sorting Kernels — Sebastian Hack, Marcel Ullrich · (2025) | TGRS Research Map | TGRS