Performance Implications of Periodic Checkpointing on Large-Scale Cluster Systems
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 18 - Volume 19
Cooperative checkpointing: a robust approach to large-scale systems reliability
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IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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The growing computational and storage needs of several scientific applications mandate the deployment of extreme-scale parallel machines, such as IBMýs BlueGene/L which can accommodate as many as 128K processors. In this paper, we present our experiences in collecting and filtering error event logs from a 8192 processor BlueGene/L prototype at IBM Rochester, which is currently ranked #8 in the Top-500 list. We analyze the logs collected from this machine over a period of 84 days starting from August 26, 2004. We perform a three-step filtering algorithm on these logs: extracting and categorizing failure events; temporal filtering to remove duplicate reports from the same location; and finally coalescing failure reports of the same error across different locations. Using this approach, we can substantially compress these logs, removing over 99.96% of the 828,387 original entries, and more accurately portray the failure occurrences on this system.