MulticoreBSP for C: A High-Performance Library for Shared-Memory Parallel Programming

The bulk synchronous parallel (BSP) model, as well as parallel programming interfaces based on BSP, classically target distributed-memory parallel architectures. In earlier work, Yzelman and Bisseling designed a MulticoreBSP for Java library specifically for shared-memory architectures. In the prese...

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Bibliographic Details
Published in:International journal of parallel programming Vol. 42; no. 4; pp. 619 - 642
Main Authors: Yzelman, A. N., Bisseling, R. H., Roose, D., Meerbergen, K.
Format: Journal Article
Language:English
Published: Boston Springer US 01.08.2014
Springer Nature B.V
Subjects:
Algorithms
C (programming language)
Communication
Computer programs
Computer Science
Costs
Distributed memory
Fourier transforms
Interfaces
Java (programming language)
Libraries
Parallel processing
Parallel programming
Processor Architectures
Python
Software
Software Engineering/Programming and Operating Systems
Studies
Synchronous
Theory of Computation
Bulk synchronous parallel
Shared-memory parallel programming
Software library
High-performance computing
Sparse matrix–vector multiplication
Fast Fourier transform
ISSN:0885-7458, 1573-7640
Online Access:Get full text
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Summary:The bulk synchronous parallel (BSP) model, as well as parallel programming interfaces based on BSP, classically target distributed-memory parallel architectures. In earlier work, Yzelman and Bisseling designed a MulticoreBSP for Java library specifically for shared-memory architectures. In the present article, we further investigate this concept and introduce the new high-performance MulticoreBSP for C library. Among other features, this library supports nested BSP runs. We show that existing BSP software performs well regardless whether it runs on distributed-memory or shared-memory architectures, and show that applications in MulticoreBSP can attain high-performance results. The paper details implementing the Fast Fourier Transform and the sparse matrix–vector multiplication in BSP, both of which outperform state-of-the-art implementations written in other shared-memory parallel programming interfaces. We furthermore study the applicability of BSP when working on highly non-uniform memory access architectures.
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ISSN:0885-7458
1573-7640
DOI:10.1007/s10766-013-0262-9