loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
2006 15th IEEE International Conference on High Performance Distributed Computing
Task Scheduling and File Replication for Data-Intensive Jobs with Batch-shared I/O
Paris
June 19-June 23
ISBN: 1-4244-0307-3
ASCII Text
x 
 
G. Khanna, N. Vydyanathan, U. Catalyurek, T. Kurc, S. Krishnamoorthy, P. Sadayappan, J. Saltz, "Task Scheduling and File Replication for Data-Intensive Jobs with Batch-shared I/O," High-Performance Distributed Computing, International Symposium on, pp. 241-252, 2006 15th IEEE International Conference on High Performance Distributed Computing, 2006.
 
 
BibTex
x
 
@article{ 10.1109/HPDC.2006.1652155,
author = {G. Khanna and N. Vydyanathan and U. Catalyurek and T. Kurc and S. Krishnamoorthy and P. Sadayappan and J. Saltz},
title = {Task Scheduling and File Replication for Data-Intensive Jobs with Batch-shared I/O},
journal ={High-Performance Distributed Computing, International Symposium on},
volume = {0},
year = {2006},
isbn = {1-4244-0307-3},
pages = {241-252},
doi = {http://doi.ieeecomputersociety.org/10.1109/HPDC.2006.1652155},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - High-Performance Distributed Computing, International Symposium on
TI - Task Scheduling and File Replication for Data-Intensive Jobs with Batch-shared I/O
SN - 1-4244-0307-3
SP241
EP252
A1 - G. Khanna,
A1 - N. Vydyanathan,
A1 - U. Catalyurek,
A1 - T. Kurc,
A1 - S. Krishnamoorthy,
A1 - P. Sadayappan,
A1 - J. Saltz,
PY - 2006
KW - BiPartition scheme
KW - task scheduling
KW - file replication
KW - data-intensive job
KW - batch-shared I/O behavior
KW - integer programming
KW - bi-level hypergraph partitioning
KW - heuristic approach
VL - 0
JA - High-Performance Distributed Computing, International Symposium on
ER -
 
G. Khanna, Dept. of Comput. Sci.&Eng., Ohio State Univ., Columbus, OH
N. Vydyanathan, Dept. of Comput. Sci.&Eng., Ohio State Univ., Columbus, OH
This paper addresses the problem of efficient execution of a batch of data-intensive tasks with batch-shared I/O behavior, on coupled storage and compute clusters. Two scheduling schemes are proposed: 1) a 0-1 integer programming (IP) based approach, which couples task scheduling and data replication, and 2) a bi-level hypergraph partitioning based heuristic approach (BiPartition), which decouples task scheduling and data replication. The experimental results show that: 1) the IP scheme achieves the best batch execution time, but has significant scheduling overhead, thereby restricting its application to small scale workloads, and 2) the BiPartition scheme is a better fit for larger workloads and systems - it has very low scheduling overhead and no more than 5-10% degradation in solution quality, when compared with the IP based approach
Index Terms:
BiPartition scheme, task scheduling, file replication, data-intensive job, batch-shared I/O behavior, integer programming, bi-level hypergraph partitioning, heuristic approach
Citation:
G. Khanna, N. Vydyanathan, U. Catalyurek, T. Kurc, S. Krishnamoorthy, P. Sadayappan, J. Saltz, "Task Scheduling and File Replication for Data-Intensive Jobs with Batch-shared I/O," hpdc, pp.241-252, 2006 15th IEEE International Conference on High Performance Distributed Computing, 2006
Usage of this product signifies your acceptance of the Terms of Use.