Author
Muhtaroğlu, Nitel, Arı, İsmail
Publication Date
2011-01
Publication Place
-
Civil-comp
Subject
Cloud computing, Finite element analysis, Paas, Structural mechanics, Calculix, Task scheduling, Multi-core, Parallel, MPI
Type
Document
Language
English
Digital
Yes
Manuscript
No
Library
Özyeğin University
Library Asset ID
1759-3433
Record ID
7de69f2c-8016-4b0e-af3a-fe6ad890d59b
Library Location
Computer Science
Date
2011-01
Notes
Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text
In this paper, we describe the challenges faced and lessons learned while establishing a large-scale high performance cloud computing service that enables online mechanical structural analysis and many other scientific applications using the finite element analysis (FEA) technique. The service is intended to process many independent and loosely-dependent (e.g. assembled system) tasks concurrently. Challenges faced include accurate job characterization, handling of many-task mixed jobs, sensitivity of task execution to multi-threading parameters, effective multi-core scheduling in a single node, and achieving seamless scale across multiple nodes. We find that significant performance gains in terms of both job completion latency and throughput are possible via dynamic or "smart" partitioning and resource-aware scheduling compared to shortest first and aggressive job scheduling techniques. We also discuss issues related to secure and private processing of sensitive models in the cloud.
