Title :
Replication-Based Fault Tolerance for MPI Applications
Author :
Walters, John Paul ; Chaudhary, Vipin
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. at Buffalo, Buffalo, NY
fDate :
7/1/2009 12:00:00 AM
Abstract :
As computational clusters increase in size, their mean time to failure reduces drastically. Typically, checkpointing is used to minimize the loss of computation. Most checkpointing techniques, however, require central storage for storing checkpoints. This results in a bottleneck and severely limits the scalability of checkpointing, while also proving to be too expensive for dedicated checkpointing networks and storage systems. We propose a scalable replication-based MPI checkpointing facility. Our reference implementation is based on LAM/MPI; however, it is directly applicable to any MPI implementation. We extend the existing state of fault-tolerant MPI with asynchronous replication, eliminating the need for central or network storage. We evaluate centralized storage, a Sun-X4500-based solution, an EMC storage area network (SAN), and the Ibrix commercial parallel file system and show that they are not scalable, particularly after 64 CPUs. We demonstrate the low overhead of our checkpointing and replication scheme with the NAS Parallel Benchmarks and the High-Performance LINPACK benchmark with tests up to 256 nodes while demonstrating that checkpointing and replication can be achieved with a much lower overhead than that provided by current techniques. Finally, we show that the monetary cost of our solution is as low as 25 percent of that of a typical SAN/parallel-file-system-equipped storage system.
Keywords :
application program interfaces; checkpointing; fault tolerance; message passing; storage management; workstation clusters; MPI application; checkpointing technique; computation loss minimisation; computational cluster; replication-based fault tolerance; storage system; Fault tolerance; MPI; checkpointing; fault-tolerance; file systems; file systems.;
Journal_Title :
Parallel and Distributed Systems, IEEE Transactions on
DOI :
10.1109/TPDS.2008.172