ASKALON: a tool set for cluster and Grid computing

被引:100
|
作者
Fahringer, T
Jugravu, A
Pllana, S
Prodan, R
Seragiotto, CJ
Truong, HL
机构
[1] Univ Innsbruck, Inst Comp Sci, A-6020 Innsbruck, Austria
[2] Univ Vienna, Inst Software Sci, A-1090 Vienna, Austria
来源
关键词
cluster computing; Grid computing; parallel and distributed applications; performance prediction; measurement and analysis; bottleneck detection; experiment management;
D O I
10.1002/cpe.929
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Performance engineering of parallel and distributed applications is a complex task that iterates through various phases, ranging from modeling and prediction, to performance measurement, experiment management, data collection, and bottleneck analysis. There is no evidence so far that all of these phases should/can be integrated into a single monolithic tool. Moreover, the emergence of computational Grids as a common single wide-area platform for high-performance computing raises the idea to provide tools as interacting Grid services that share resources, support interoperability among different users and tools, and, most importantly, provide omnipresent services over the Grid. We have developed the ASKALON tool set to support performance-oriented development of parallel and distributed (Grid) applications. ASKALON comprises four tools, coherently integrated into a service-oriented architecture. SCALEA is a performance instrumentation, measurement, and analysis tool of parallel and distributed applications. ZENTURIO is a general purpose experiment management tool with advanced support for multi-experiment performance analysis and parameter studies. AKSUM provides semi-automatic highlevel performance bottleneck detection through a special-purpose performance property specification language. The PerformanceProphet enables the user to model and predict the performance of parallel applications at the early stages of development. In this paper we describe the overall architecture of the ASKALON tool set and outline the basic functionality of the four constituent tools. The structure of each tool is based on the composition and sharing of remote Grid services, thus enabling tool interoperability. In addition, a data repository allows the tools to share the common application performance and output data that have been derived by the individual tools. A service repository is used to store common portable Grid service implementations. A general-purpose Factory service is employed to create service instances on arbitrary remote Grid sites. Discovering and dynamically binding to existing remote services is achieved through registry services. The ASKALON visualization diagrams support both online and postmortem visualization of performance and output data. We demonstrate the usefulness and effectiveness of ASKALON by applying the tools to real-world applications. Copyright (C) 2005 John Wiley Sons, Ltd.
引用
收藏
页码:143 / 169
页数:27
相关论文
共 50 条
  • [1] ASKALON: A grid application development and computing environment
    Fahringer, T
    Prodan, R
    Duan, RB
    Nerieri, F
    Podlipnig, S
    2005 6TH INTERNATIONAL WORKSHOP ON GRID COMPUTING (GRID), 2005, : 122 - 131
  • [2] Grid and Cluster Computing
    Priol, T
    Lee, C
    Schwiegelshosh, U
    Puppin, D
    EURO-PAR 2004 PARALLEL PROCESSING, PROCEEDINGS, 2004, 3149 : 398 - 398
  • [3] Grid and cluster computing: Introduction
    Lect. Notes Comput. Sci., 2007, (359):
  • [4] Grid, Cluster and Cloud Computing
    Keahey, K.
    Laforenza, D.
    Reinefeld, A.
    Ritrovato, P.
    Thain, D.
    Wilkins-Diehr, N.
    EURO-PAR 2010 PARALLEL PROCESSING, PT I, 2010, 6271 : 341 - +
  • [5] WORKFLOW MONITORING AND ANALYSIS TOOL FOR ASKALON
    Ostermann, Simon
    Plankensteiner, Kassian
    Prodan, Radu
    Fahringer, Thomas
    Iosup, Alexandru
    GRID AND SERVICES EVOLUTION, 2009, : 73 - 86
  • [6] The Differences Among Cloud Computing, Cluster Computing And Grid Computing
    Wang, Mu-kuai
    Li, Dao-guo
    Fu, Bin
    2010 INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE AND ENGINEERING (MSE 2010), VOL 3, 2010, : 78 - 81
  • [7] Cluster computing as a teaching tool
    Anshus, OJ
    Elster, AC
    Vinter, B
    PARALLEL COMPUTING: SOFTWARE TECHNOLOGY, ALGORITHMS, ARCHITECTURES AND APPLICATIONS, 2004, 13 : 887 - 894
  • [8] Grid, Cluster, and Cloud Computing Introduction
    Weissman, Jon
    Wolters, Lex
    Abramson, David
    Humphrey, Marty
    EURO-PAR 2009: PARALLEL PROCESSING, PROCEEDINGS, 2009, 5704 : 389 - 389
  • [9] The anatomy of a course in cluster and grid computing
    Yang, CT
    Li, KC
    ITRE 2005: 3rd International Conference on Information Technology: Research and Education, Proceedings, 2005, : 403 - 407
  • [10] Topic 6 -: Grid and cluster computing
    Badia, Rosa M.
    Perez, Christian
    Andrzejak, Artur
    Arenas, Alvaro
    Euro-Par 2007 Parallel Processing, Proceedings, 2007, 4641 : 359 - 359