Implementing micro High Performance Computing (μHPC) artifact: Affordable HPC Facilities for Academia

被引:0
|
作者
Mwasaga, Nkundwe Moses [1 ]
Joy, Mike [2 ]
机构
[1] Univ Eastern Finland, Sch Comp, Joensuu, Finland
[2] Univ Warwick, Comp Sci, Coventry, W Midlands, England
关键词
micro HPC; Beowulf cluster; constructivism; parallel computation; High Performance Computation; scalability; credit card-sized PC; TECHNOLOGY; ACCEPTANCE;
D O I
暂无
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
This Research to Practice Full Paper presents the experience of implementing micro HPC (mu HPC) clusters in the education context. In developing countries, access to and experience of High Performance Computing (HPC) facilities (which are important for the economic development of those countries) has presented challenges to academic institutions due to prohibitive costs of acquisition and maintenance of HPC systems. These challenges affect the delivery of courses, which include HPC and parallel computation in their syllabi. However, due to advancements in integrated circuit technologies, creditcard-sized personal computers (PCs) have emerged with the capabilities of a fully-fledged PC. These credit-card-sized PCs offer an opportunity for system integrators to build micro HPC (mu HPC) clusters which, apart from their efficiency, scalability and availability, have a number of attributes which are not shared with conventional data-center based HPC clusters These include their low power consumption, portability, diskless nodes, cost-effectiveness and excellent price to performance ratios. mu HPC clusters are, therefore, ideally suited to support curricula in all educational disciplines that demand parallel computation. The purpose of this study is to investigate the implementation of mu HPC to find out from students how ease of use of a mu HPC system is to acquire skills and knowledge of HPC. We used focus groups and surveys to gather data in the framework of the design science research paradigm. The implementation of mu HPC clusters involved a demonstration of the system in the problem context that provided valuable lessons. The results indicate that mu HPC is the ease of use HPC artifact for learning about management, integration, deployment, installation, downloading, and running of parallel programs.
引用
收藏
页数:9
相关论文
共 50 条
  • [41] ELIXIR-IT HPC@CINECA: high performance computing resources for the bioinformatics community
    Tiziana Castrignanò
    Silvia Gioiosa
    Tiziano Flati
    Mirko Cestari
    Ernesto Picardi
    Matteo Chiara
    Maddalena Fratelli
    Stefano Amente
    Marco Cirilli
    Marco Antonio Tangaro
    Giovanni Chillemi
    Graziano Pesole
    Federico Zambelli
    BMC Bioinformatics, 21
  • [42] On-demand Data Analytics in HPC Environments at Leadership Computing Facilities: Challenges and Experiences
    Harney, John
    Lim, Seung-Hwan
    Sukumar, Sreenivas
    Stansberry, Dale
    Xenopoulos, Peter
    2016 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2016, : 2087 - 2096
  • [43] CLOUDRB: A framework for scheduling and managing High-Performance Computing (HPC) applications in science cloud
    Somasundaram, Thamarai Selvi
    Govindarajan, Kannan
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2014, 34 : 47 - 65
  • [44] Application of multivariate time-series model for high performance computing (HPC) fault prediction
    Pei, Xiangdong
    Yuan, Min
    Mao, Guo
    Pang, Zhengbin
    PLOS ONE, 2023, 18 (10):
  • [45] HPC/PF - High Performance Computing Platform: An Environment That Accelerates Large-Scale Simulations
    Ono, Kenji
    Kawanabe, Tomohiro
    Hatada, Toshio
    HIGH PERFORMANCE COMPUTING FOR COMPUTATIONAL SCIENCE - VECPAR 2012, 2013, 7851 : 23 - 27
  • [46] ROBIOCLUSTER - an open source platform for HPC (high performance computing)/Linux clusters in the biomedical field
    Marusteri, Marius
    Crainicu, Bogdan
    Schiopu, Alexandru
    INTEGRATING BIOMEDICAL INFORMATION: FROM E-CELL TO E-PATIENT, 2006, : 174 - 177
  • [47] Guest Editorial High Performance Computing (HPC) Applications for a More Resilient and Efficient Power Grid
    Huang, Zhenyu
    Tate, Zeb
    Abhyankar, Shrirang
    Dong, Zhaoyang
    Khaitan, Siddhartha
    Min, Liang
    Taylor, Gary
    IEEE TRANSACTIONS ON SMART GRID, 2017, 8 (03) : 1363 - 1365
  • [48] Cost-oriented proactive fault tolerance approach to high performance computing (HPC) in the cloud
    Egwutuoha, Ifeanyi P.
    Chen, Shiping
    Levy, David
    Selic, Bran
    Calvo, Rafael
    INTERNATIONAL JOURNAL OF PARALLEL EMERGENT AND DISTRIBUTED SYSTEMS, 2014, 29 (04) : 363 - 378
  • [49] HPC-ICTM: The interval categorizer tessellation-based model for high performance computing
    de Aguiar, Marilton S.
    Dimuro, Gracaliz P.
    Costa, Fabia A.
    Silva, Rafael K. S.
    De Rose, Cesar A. F.
    Costa, Antonio C. R.
    Kreinovich, Vladik
    APPLIED PARALLEL COMPUTING: STATE OF THE ART IN SCIENTIFIC COMPUTING, 2006, 3732 : 83 - 92
  • [50] Empirical Performance Analysis of HPC Benchmarks Across Variations in Cloud Computing
    Ahuja, Sanjay P.
    Mani, Sindhu
    INTERNATIONAL JOURNAL OF CLOUD APPLICATIONS AND COMPUTING, 2013, 3 (01) : 13 - 26