Performance Analysis of Alternative Open Source Parallel Computing Approach to OpenMP on Multicore Processors

被引:0
|
作者
Chickerur, Satyadhyan [1 ]
Rayudu, Dadi Mohan Krishna [2 ]
Hiriyannaiah, Srinidhi [2 ]
Shabalina, Olga [3 ]
机构
[1] BV Bhoomaraddi Coll Engn & Technol, Ctr High Performance Comp, Hubli, India
[2] IBM ISL, Bangalore, Karnataka, India
[3] Volgograd State Tech Univ, Comp Aided Design Dept, Volgograd, Russia
关键词
Parallel programming; Clang; OpenMP; Grand Central Dispatch;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this era of evolving computing field, parallel computing is one of the fastest changing fields. There have been numerous researches made and still the research is going on in the areas of data decomposition, parallel algorithms to get more performance through parallelism. In this paper we have achieved parallelism by using an open source made available with the name libdispatch (implementation of Grand Central Dispatch Services). This package has been ported to the FreeBSD, however this can also be used under open source environment. In this paper we have experimented with matrix multiplication in sequential and parallel programs. The categories of experimentation done are: Sequential Programming with GCC and Clang; Parallel programming with OpenMP and clang with dispatcher. Better performance has been observed in Clang for both sequential and parallel computations
引用
收藏
页码:466 / 476
页数:11
相关论文
共 50 条
  • [1] Performance of OpenMP benchmarks on Multicore processors
    Marowka, Ami
    ALGORITHMS AND ARCHITECTURES FOR PARALLEL PROCESSING, PROCEEDINGS, 2008, 5022 : 208 - +
  • [2] Enabling performance portability of data-parallel OpenMP applications on asymmetric multicore processors
    Carlos Saez, Juan
    Castro, Fernando
    Prieto-Matias, Manuel
    PROCEEDINGS OF THE 49TH INTERNATIONAL CONFERENCE ON PARALLEL PROCESSING, ICPP 2020, 2020,
  • [3] Concurrent Parallel Processing on Graphics and Multicore Processors with OpenACC and OpenMP
    Stone, Christopher P.
    Davis, Roger L.
    Lee, Daryl Y.
    ACCELERATOR PROGRAMMING USING DIRECTIVES, WACCPD 2017, 2018, 10732 : 103 - 122
  • [4] An approach of performance comparisons with OpenMP and CUDA parallel programming on multicore systems
    Chang, Chih-Hung
    Lu, Chih-Wei
    Yang, Chao-Tung
    Chang, Tzu-Chieh
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2016, 28 (16): : 4230 - 4245
  • [5] Performance comparison of open-source parallel sorting with OpenMP
    Umeda, Takayuki
    Oya, Shuhei
    PROCEEDINGS OF 2015 THIRD INTERNATIONAL SYMPOSIUM ON COMPUTING AND NETWORKING (CANDAR), 2015, : 334 - 340
  • [6] Multicore processors and GPUs: the power of parallel computing in the Cloud
    Bennett, Kelly W.
    Robertson, James
    ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING FOR MULTI-DOMAIN OPERATIONS APPLICATIONS II, 2020, 11413
  • [7] Evaluation of Multicore Processors for Embedded Systems by Parallel Benchmark Program Using OpenMP
    Hanawa, Toshihiro
    Sato, Mitsuhisa
    Lee, Jinpil
    Imada, Takayuki
    Kimura, Hideaki
    Boku, Taisuke
    EVOLVING OPENMP IN AN AGE OF EXTREME PARALLELISM, 2009, 5568 : 15 - 27
  • [8] Performance analysis and multicore processors
    Carleton, G
    Shands, W
    DR DOBBS JOURNAL, 2006, 31 (05): : 22 - +
  • [9] PERFORMANCE ANALYSIS AND COMPARISON OF PARALLEL COMPUTING FRAMEWORKS:SIPS AND OPENMP
    Kaur, Likhilpreet
    Kumar, Anil
    PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICCS), 2019, : 711 - 718
  • [10] Comparison and analysis of parallel computing performance using OpenMP and MPI
    Hua, Shen
    Yang, Zhang
    Open Automation and Control Systems Journal, 2013, 5 (01): : 38 - 44