Issue No. 04 - April (2009 vol. 20)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPDS.2008.128
Yawei Li , Illinois Institute of Technology, Chicago
Zhiling Lan , Illinois Institute of Technology, Chicago
Prashasta Gujrati , Illinois Institute of Technology, Chicago
Xian-He Sun , Illinois Institute of Technology, Chicago
As the scale of parallel systems continues to grow, fault management of these systems is becoming a critical challenge. While existing research mainly focuses on developing or improving fault tolerance techniques, a number of key issues remain open. In this paper, we propose runtime strategies for spare node allocation and job rescheduling in response to failure prediction. These strategies, together with failure predictor and fault tolerance techniques, construct a runtime system called FARS (Fault-Aware Runtime System). In particular, we propose a 0-1 knapsack model and demonstrate its flexibility and effectiveness for reallocating running jobs to avoid failures. Experiments, by means of synthetic data and real traces from production systems, show that FARS has the potential to significantly improve system productivity (i.e., performance and reliability).
Scheduling, Fault-tolerance, Parallel systems, Performance
P. Gujrati, Z. Lan, Y. Li and X. Sun, "Fault-Aware Runtime Strategies for High-Performance Computing," in IEEE Transactions on Parallel & Distributed Systems, vol. 20, no. , pp. 460-473, 2008.