On the Easy Use of Scientific Computing Services for Large Scale Linear Algebra and Parallel Decision Making with the P-Grade Portal

  • Authors:

  • Hrachya Astsatryan;Vladimir Sahakyan;Yuri Shoukouryan;Michel Daydé;Aurelie Hurault;Ronan Guivarch;Harutyun Terzyan;Levon Hovhannisyan

  • Affiliations:

  • Institute for Informatics and Automation Problems of the National Academy of Sciences of the Republic of Armenia, Yerevan, Armenia 0014;Institute for Informatics and Automation Problems of the National Academy of Sciences of the Republic of Armenia, Yerevan, Armenia 0014;Institute for Informatics and Automation Problems of the National Academy of Sciences of the Republic of Armenia, Yerevan, Armenia 0014;University of Toulouse, INPT (ENSEEIHT)-IRIT, Toulouse, France 31071;University of Toulouse, INPT (ENSEEIHT)-IRIT, Toulouse, France 31071;University of Toulouse, INPT (ENSEEIHT)-IRIT, Toulouse, France 31071;State Engineering University of Armenia, Yerevan, Armenia 0009;State Engineering University of Armenia, Yerevan, Armenia 0009

  • Venue:
  • Journal of Grid Computing
  • Year:
  • 2013

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Abstract

Scientific research is becoming increasingly dependent on the large-scale analysis of data using distributed computing infrastructures (Grid, cloud, GPU, etc.). Scientific computing (Petitet et al. 1999) aims at constructing mathematical models and numerical solution techniques for solving problems arising in science and engineering. In this paper, we describe the services of an integrated portal based on the P-Grade (Parallel Grid Run-time and Application Development Environment) portal ( http://www.p-grade.hu ) that enables the solution of large-scale linear systems of equations using direct solvers, makes easier the use of parallel block iterative algorithm and provides an interface for parallel decision making algorithms. The ultimate goal is to develop a single sign on integrated multi-service environment providing an easy access to different kind of mathematical calculations and algorithms to be performed on hybrid distributed computing infrastructures combining the benefits of large clusters, Grid or cloud, when needed.