Study of parallel programming models on computer clusters with Intel MIC coprocessors

Coprocessors based on the Intel Many Integrated Core (MIC) Architecture have been adopted in many high-performance computer clusters. Typical parallel programming models, such as MPI and OpenMP, are supported on MIC processors to achieve the parallelism. In this work, we conduct a detailed study on...

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Bibliographic Details
Published in:The international journal of high performance computing applications 2017-07, Vol.31 (4), p.303-315
Main Authors: Huang, Miaoqing, Lai, Chenggang, Shi, Xuan, Hao, Zhijun, You, Haihang
Format: Article
Language:English
Subjects:
Central processing units
Clusters
Computer architecture
Coprocessors
CPUs
Data processing
Microprocessors
Parallel programming
Performance enhancement
Processors
Product development
Web content delivery
Workload
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Summary:Coprocessors based on the Intel Many Integrated Core (MIC) Architecture have been adopted in many high-performance computer clusters. Typical parallel programming models, such as MPI and OpenMP, are supported on MIC processors to achieve the parallelism. In this work, we conduct a detailed study on the performance and scalability of the MIC processors under different programming models using the Beacon computer cluster. Our findings are as follows. (1) The native MPI programming model on the MIC processors is typically better than the offload programming model, which offloads the workload to MIC cores using OpenMP. (2) On top of the native MPI programming model, multithreading inside each MPI process can further improve the performance for parallel applications on computer clusters with MIC coprocessors. (3) Given a fixed number of MPI processes, it is a good strategy to schedule these MPI processes to as few MIC processors as possible to reduce the cross-processor communication overhead. (4) The hybrid MPI programming model, in which data processing is distributed to both MIC cores and CPU cores, can outperform the native MPI programming model.
ISSN:1094-3420
1741-2846
DOI:10.1177/1094342015580864