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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 95
PROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED, GRID AND CLOUD COMPUTING FOR ENGINEERING
Edited by: P. Iványi and B.H.V. Topping
Paper 87

Smart Job Scheduling for High-Performance Cloud Computing Services

N. Muhtaroglu and I. Ari

Ozyegin University, Turkey

Full Bibliographic Reference for this paper
N. Muhtaroglu, I. Ari, "Smart Job Scheduling for High-Performance Cloud Computing Services", in P. Iványi, B.H.V. Topping, (Editors), "Proceedings of the Second International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 87, 2011. doi:10.4203/ccp.95.87
Keywords: cloud computing, finite element analysis, PaaS, structural mechanics, CalculiX, task scheduling, multi-core, parallel, MPI.

Summary
According to the U.S. National Institute of Standards and Technology (NIST): "Cloud Computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources ...that can be rapidly provisioned and released with minimal management effort". NIST further differentiates cloud as having "five essential characteristics, three service models, and four deployment models". Cloud services should essentially have on-demand network-based accessibility, resource pooling and rapid elasticity characteristics, could be provided via software, platform or infrastructure as-a-service models, and be made available through private, community, public or hybrid deployments. Our experience with the engineering and scientific communities revealed the need for cloud computing (CC) services that can be shared for solving common problems in different disciplines.

Our contributions are as follows:

  • The design of a new online FEA cloud service.
  • Performance characterization over parallel (multi-core) and distributed (multi-node) resources.
  • A comprehensive evaluation of alternative job execution strategies for different FEA jobs.
  • Concurrent execution of batches and mixes of jobs to enable high-performance many-task job processing.
  • Comparisons of different scheduling approaches.
  • Integration of SPOOLES Message Passing Interface (MPI) version into CalculiX FEA tool.

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