Efficient parallel algorithms can be made robust |
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Authors: | Paris C Kanellakis Alex A Shvartsman |
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Affiliation: | (1) Department of Computer Science, Brown University, PO Box 1910, 02912 Providence, RI, USA;(2) Digital Equipment Corporation, LKG2-2/T2, 550 King Street, 01460 Littleton, MA, USA |
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Abstract: | Summary The efficient parallel algorithms proposed for many fundamental problems, such as list ranking, integer sorting and computing preorder numberings on trees, are very sensitive to processor failures. The requirement of efficiency (commonly formalized usingParallel-timexProcessors as a cost measure) has led to the design of highly tuned PRAM algorithms which, given the additional constraint of simple processor failures, unfortunately become inefficient or even incorrect. We propose a new notion ofrobustness, that combines efficiency with fault tolerance. For the common case of fail-stop errors, we develop a general and easy to implement technique to make robust many efficient parallel algorithms, e.g., algorithms for all the problems listed above. More specifically,for any dynamic pattern of fail-stop errors on a CRCW PRAMwith at least one surviving processor, our method increases the original algorithm cost by at most a log2 multiplicative factor. Our technique is based on a robust solution of the problem ofWrite-All, i.e., usingP processors, write 1's in all locations of anN-sized array. In addition we show that at least a log/log log multiplicative overhead will be incurred for certain patterns of failures by any algorithm that implements robust solutions toWrite-All withP=N. However, by exploiting parallel slackness, we obtain an optimal cost algorithm when
Paris C. Kanellakis is a professor of computer science at Brown University. His primary research interests are in the application of logic to computer science, such as high-level query languages for database systems, parallel evaluation of logic programs, and type inference for programming languages. He has published many articles on these subjects and is the author of the chapter Elements of Relational Database Theory in theHandbook of Theoretical Computer Science (Elsevier, 1990). He has also contributed to the theory of distributed computing and to combinatorial optimization.
Alex Allister Shvartsman is an engineer at Digital Equipment Corporation. His professional interests include design and development of efficient distributed systems, distributed resource management, and theoretical foundations of fault-tolerant parallel computation. At Digital he architected and managed the development of distributed control systems that automated several of Digital's manufacturing processes. He is currently on an academic leave at Brown University.An extended abstract of a part of this work appears as: Kanellakis and Shvartsman (1989) in the Proceedings of the 8th ACM Symposium on Principles of Distributed Computing, Edmonton 1989This author was supported by NSF grant IRI-8617344, an Alfred P. Sloan fellowship and ONR grant N00014-83-K-0146 ARPA Order No. 4786This author was supported by DEC GEEP Doctoral program and ONR grant N00014-91-J-1613 |
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Keywords: | Parallel computation Fault tolerance Computation complexity Lower bounds Robust algorithms |
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