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MND-MST: A multi-node multi-device parallel Boruvka’s MST algorithm

Panja, R and Vadhiyar, S (2018) MND-MST: A multi-node multi-device parallel Boruvka’s MST algorithm. In: 47th International Conference on Parallel Processing, ICPP 2018, 14 - 16 August 2018, Eugene.

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Official URL: https://doi.org/10.1145/3225058.3225146


Efficient processing of large-scale graph applications on heterogeneous CPU-GPU systems require effectively harnessing the combined power of both the CPU and GPU devices. Finding minimum spanning tree (MST) is an important graph application and is used in different domains. When applying MST algorithms for large-scale graphs across multiple nodes (or machines), the existing approaches use BSP (bulk synchronous parallel) model involving large-scale communications. In this paper, we propose a multi-node multi-device algorithm for MST, MND-MST, that uses a divide-and-conquer approach by partitioning the input graph across multiple nodes and devices and performing independent Boruvka’s MST computations on the devices. The results from the different nodes are merged using a novel hybrid merging algorithm that ensures that the combined results on a node never exceeds it memory capacity. The algorithm also simultaneously harnesses both CPU and GPU devices. In our experiments, we show that our proposed algorithm shows 24-88% performance improvements over an existing BSP approach. We also show that the algorithm exhibits almost linear scalability, and the use of GPUs result in upto 23% improvement in performance over multi-node CPU-only performance.

Item Type: Conference Paper
Publication: ACM International Conference Proceeding Series
Publisher: Association for Computing Machinery
Additional Information: The copyright for this article belongs to the Association for Computing Machinery.
Keywords: Graphics processing unit; Program processors; Trees (mathematics), Bulk synchronous parallel; Conquer; Divide; Divide-and-conquer approach; Minimum spanning trees; Multi-devices; Multi-nodes; Performance improvements, Graph theory
Department/Centre: Division of Interdisciplinary Sciences > Computational and Data Sciences
Division of Interdisciplinary Sciences > Supercomputer Education & Research Centre
Date Deposited: 05 Aug 2022 11:40
Last Modified: 05 Aug 2022 11:40
URI: https://eprints.iisc.ac.in/id/eprint/75410

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