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Autores principales: Kurpicz, Florian, Mehnert, Pascal, Sanders, Peter, Schimek, Matthias
Formato: Preprint
Publicado: 2024
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Acceso en línea:https://arxiv.org/abs/2404.16517
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author Kurpicz, Florian
Mehnert, Pascal
Sanders, Peter
Schimek, Matthias
author_facet Kurpicz, Florian
Mehnert, Pascal
Sanders, Peter
Schimek, Matthias
contents String sorting is an important part of tasks such as building index data structures. Unfortunately, current string sorting algorithms do not scale to massively parallel distributed-memory machines since they either have latency (at least) proportional to the number of processors $p$ or communicate the data a large number of times (at least logarithmic). We present practical and efficient algorithms for distributed-memory string sorting that scale to large $p$. Similar to state-of-the-art sorters for atomic objects, the algorithms have latency of about $p^{1/k}$ when allowing the data to be communicated $k$ times. Experiments indicate good scaling behavior on a wide range of inputs on up to 49152 cores. Overall, we achieve speedups of up to 5 over the current state-of-the-art distributed string sorting algorithms.
format Preprint
id arxiv_https___arxiv_org_abs_2404_16517
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Scalable Distributed String Sorting
Kurpicz, Florian
Mehnert, Pascal
Sanders, Peter
Schimek, Matthias
Data Structures and Algorithms
String sorting is an important part of tasks such as building index data structures. Unfortunately, current string sorting algorithms do not scale to massively parallel distributed-memory machines since they either have latency (at least) proportional to the number of processors $p$ or communicate the data a large number of times (at least logarithmic). We present practical and efficient algorithms for distributed-memory string sorting that scale to large $p$. Similar to state-of-the-art sorters for atomic objects, the algorithms have latency of about $p^{1/k}$ when allowing the data to be communicated $k$ times. Experiments indicate good scaling behavior on a wide range of inputs on up to 49152 cores. Overall, we achieve speedups of up to 5 over the current state-of-the-art distributed string sorting algorithms.
title Scalable Distributed String Sorting
topic Data Structures and Algorithms
url https://arxiv.org/abs/2404.16517