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Algorithm Engineering and Experimentation

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Produktnummer: 186ff9aebe4643438486673618af6b3d12
Themengebiete: Approximation Algorithms Combinatorial Algorithms Computational Complexity Data Structures Geometric Algorithms algorithm analysis and problem complexity algorithms computational geometry
Veröffentlichungsdatum: 29.06.1999
EAN: 9783540662273
Sprache: Englisch
Seitenzahl: 356
Produktart: Kartoniert / Broschiert
Herausgeber: Goodrich, Michael T. McGeoch, Catherine C.
Verlag: Springer Berlin
Untertitel: International Workshop ALENEX'99 Baltimore, MD, USA, January 15-16, 1999, Selected Papers
Produktinformationen "Algorithm Engineering and Experimentation"
Symmetric multiprocessors (SMPs) dominate the high-end server market and are currently the primary candidate for constructing large scale multiprocessor systems. Yet, the design of e cient parallel algorithms for this platform c- rently poses several challenges. The reason for this is that the rapid progress in microprocessor speed has left main memory access as the primary limitation to SMP performance. Since memory is the bottleneck, simply increasing the n- ber of processors will not necessarily yield better performance. Indeed, memory bus limitations typically limit the size of SMPs to 16 processors. This has at least twoimplicationsfor the algorithmdesigner. First, since there are relatively few processors availableon an SMP, any parallel algorithm must be competitive with its sequential counterpart with as little as one processor in order to be r- evant. Second, for the parallel algorithm to scale with the number of processors, it must be designed with careful attention to minimizing the number and type of main memory accesses. In this paper, we present a computational model for designing e cient al- rithms for symmetric multiprocessors. We then use this model to create e cient solutions to two widely di erent types of problems - linked list pre x com- tations and generalized sorting. Both problems are memory intensive, but in die rent ways. Whereas generalized sorting algorithms typically require a large numberofmemoryaccesses, they areusuallytocontiguousmemorylocations. By contrast, prex computation algorithms typically require a more modest qu- tity of memory accesses, but they are are usually to non-contiguous memory locations.

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