Optimizing Tensor Contraction Paths: A Greedy Algorithm Approach With Improved Cost Functions

Fuente: arXiv
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Hauptverfasser: Orgler, Sheela, Blacher, Mark
Format: Preprint
Veröffentlicht: 2024
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author Orgler, Sheela
Blacher, Mark
author_facet Orgler, Sheela
Blacher, Mark
contents Finding efficient tensor contraction paths is essential for a wide range of problems, including model counting, quantum circuits, graph problems, and language models. There exist several approaches to find efficient paths, such as the greedy and random greedy algorithm by Optimized Einsum (opt_einsum), and the greedy algorithm and hypergraph partitioning approach employed in cotengra. However, these algorithms require a lot of computational time and resources to find efficient contraction paths. In this paper, we introduce a novel approach based on the greedy algorithm by opt_einsum that computes efficient contraction paths in less time. Moreover, with our approach, we are even able to compute paths for large problems where modern algorithms fail.
format Preprint
id arxiv_https___arxiv_org_abs_2405_09644
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Optimizing Tensor Contraction Paths: A Greedy Algorithm Approach With Improved Cost Functions
Orgler, Sheela
Blacher, Mark
Quantum Physics
Discrete Mathematics
Mathematical Software
Finding efficient tensor contraction paths is essential for a wide range of problems, including model counting, quantum circuits, graph problems, and language models. There exist several approaches to find efficient paths, such as the greedy and random greedy algorithm by Optimized Einsum (opt_einsum), and the greedy algorithm and hypergraph partitioning approach employed in cotengra. However, these algorithms require a lot of computational time and resources to find efficient contraction paths. In this paper, we introduce a novel approach based on the greedy algorithm by opt_einsum that computes efficient contraction paths in less time. Moreover, with our approach, we are even able to compute paths for large problems where modern algorithms fail.
title Optimizing Tensor Contraction Paths: A Greedy Algorithm Approach With Improved Cost Functions
topic Quantum Physics
Discrete Mathematics
Mathematical Software
url https://arxiv.org/abs/2405.09644