Combinatorial BLAS 2.0: Scaling Combinatorial Algorithms on Distributed-Memory Systems

Combinatorial algorithms such as those that arise in graph analysis, modeling of discrete systems, bioinformatics, and chemistry, are often hard to parallelize. The Combinatorial BLAS library implements key computational primitives for rapid development of combinatorial algorithms in distributed-mem...

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Veröffentlicht in:IEEE transactions on parallel and distributed systems Jg. 33; H. 4; S. 989 - 1001
Hauptverfasser: Azad, Ariful, Selvitopi, Oguz, Hussain, Md Taufique, Gilbert, John R., Buluc, Aydn
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.04.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Bioinformatics
Combinatorial analysis
combinatorics
communication-avoidance algorithms
Computational modeling
Data analysis
Data structures
Discrete systems
Distributed memory
graph theory
Indexes
Libraries
parallel computing
Parallel processing
Sparse matrices
Three-dimensional displays
ISSN:1045-9219, 1558-2183
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Zusammenfassung:Combinatorial algorithms such as those that arise in graph analysis, modeling of discrete systems, bioinformatics, and chemistry, are often hard to parallelize. The Combinatorial BLAS library implements key computational primitives for rapid development of combinatorial algorithms in distributed-memory systems. During the decade since its first introduction, the Combinatorial BLAS library has evolved and expanded significantly. This article details many of the key technical features of Combinatorial BLAS version 2.0, such as communication avoidance, hierarchical parallelism via in-node multithreading, accelerator support via GPU kernels, generalized semiring support, implementations of key data structures and functions, and scalable distributed I/O operations for human-readable files. Our article also presents several rules of thumb for choosing the right data structures and functions in Combinatorial BLAS 2.0, under various common application scenarios.
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ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2021.3094091