Abstract
As cluster sizes head into tens of thousands, current job launch mechanisms do not scale as they are limited by resource constraints as well as performance bottlenecks. The job launch process includes two phases – spawning of processes on processors and information exchange between processes for job initialization. Implementations of various programming models follow distinct protocols for the information exchange phase. We present the design of a scalable, extensible and high-performance job launch architecture for very large scale parallel computing. We present implementations of this architecture which achieve a speedup of more than 700% in launching a simple Hello World MPI application on 10,240 processor cores and also scale to more than 3 times the number of processor cores compared to prior solutions.
This research is supported in part by U.S. Department of Energy grants #DE-FC02-06ER25749 and #DE-FC02-06ER25755; National Science Foundation grants #CNS-0403342 and #CCF-0702675; grant from Wright Center for Innovation #WCI04-010-OSU-0; grants from Intel, Mellanox, Cisco, and Sun Microsystems; Equipment donations from Intel, Mellanox, AMD, Advanced Clustering, Appro, QLogic, and Sun Microsystems.
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Sridhar, J.K., Koop, M.J., Perkins, J.L., Panda, D.K. (2008). ScELA: Scalable and Extensible Launching Architecture for Clusters. In: Sadayappan, P., Parashar, M., Badrinath, R., Prasanna, V.K. (eds) High Performance Computing - HiPC 2008. HiPC 2008. Lecture Notes in Computer Science, vol 5374. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89894-8_30
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DOI: https://doi.org/10.1007/978-3-540-89894-8_30
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