NDLI: Efficient Runtime Environment for Coupled Multi-physics Simulations: Dynamic Resource Allocation and Load-Balancing

Content Provider	IEEE Xplore Digital Library
Author	Soon-Heum Ko Nayong Kim Joohyun Kim Thota, A. Jha, S.
Copyright Year	2010
Abstract	Coupled Multi-Physics simulations, such as hybrid CFD-MD simulations, represent an increasingly important class of scientific applications. Often the physical problems of interest demand the use of high-end computers, such as TeraGrid resources, which are often accessible only via batch-queues. Batch-queue systems are not developed to natively support the coordinated scheduling of jobs – which in turn is required to support the concurrent execution required by coupled multi-physics simulations. In this paper we develop and demonstrate a novel approach to overcome the lack of native support for coordinated job submission requirement associated with coupled runs. We establish the performance advantages arising from our solution, which is a generalization of the Pilot-Job concept – which in of itself is not new, but is being applied to coupled simulations for the first time. Our solution not only overcomes the initial co-scheduling problem, but also provides a dynamic resource allocation mechanism. Support for such dynamic resources is critical for a load balancing mechanism, which we develop and demonstrate to be effective at reducing the total time-to-solution of the problem. We establish that the performance advantage of using Big Jobs is invariant with the size of the machine as well as the size of the physical model under investigation. The Pilot-Job abstraction is developed using SAGA, which provides an infrastructure agnostic implementation, and which can seamlessly execute and utilize distributed resources.
Starting Page	349
Ending Page	358
File Size	1444231
Page Count	10
File Format	PDF
ISBN	9781424469871
e-ISBN	9781424469888
DOI	10.1109/CCGRID.2010.107
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-17
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Runtime environment Resource management Computational modeling Computational fluid dynamics Biological system modeling Computer simulation Grid computing Physics computing Processor scheduling Biology computing Co-allocation SAGA (Simple API for Grid Applications) BigJob Hybrid CFD-MD Approach Runtime Environment Load Balancing
Content Type	Text
Resource Type	Article

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