Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures 2018
DOI: 10.1145/3210377.3210390
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Parallel Working-Set Search Structures

Abstract: In this paper 1 we present two versions of a parallel working-set map on p processors that supports searches, insertions and deletions. In both versions, the total work of all operations when the map has size at least p is bounded by the working-set bound, i.e., the cost of an item depends on how recently it was accessed (for some linearization): accessing an item in the map with recency r takes O(1+logr ) work. In the simpler version each map operation has O (logp) 2 + logn span (where n is the maximum size o… Show more

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Cited by 6 publications
(21 citation statements)
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References 34 publications
(42 reference statements)
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“…However, they are not work-efficient, requiring O(m log n) work. There is also previous work focusing on I/O efficiency [15] and concurrent operations [37,57] for parallel trees, and parallel data structures supporting batches [4,64,78]. Some previous algorithms achieve optimal work and polylogarithmic span.…”
Section: Background and Related Workmentioning
confidence: 99%
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“…However, they are not work-efficient, requiring O(m log n) work. There is also previous work focusing on I/O efficiency [15] and concurrent operations [37,57] for parallel trees, and parallel data structures supporting batches [4,64,78]. Some previous algorithms achieve optimal work and polylogarithmic span.…”
Section: Background and Related Workmentioning
confidence: 99%
“…All the above-mentioned algorithms have O(log m log n) span in the binary-forking model. There have also been parallel bulk operations for self-adjusting data structures [4]. As far as we know, there is no parallel algorithm for ordered set functions (Union, Intersection and Difference) with optimal work and O(log n) span in the binary-forking model.…”
Section: Background and Related Workmentioning
confidence: 99%
“…Searches are easy, and pose no problem for a multithreaded implementation. But performing a sorted batch of b insertions or deletions on the PVW 2-3 tree with n items essentially involves spawning O(log b) synchronous waves of structural changes from the bottom of the 2-3 tree upwards to the root, each wave taking O (1) steps to move up one level. This relies crucially on the lock-step synchronicity of the processors to ensure that these waves never overlap, and naively attempting to use locking to prevent waves from overlapping will cause the worst-case span to increase from O(log b…”
Section: Related Workmentioning
confidence: 99%
“…We shall work within the QRMW PPM model that was introduced in [1] as a more realistic PPM (parallel pointer machine) model for parallel programming. Unrealistic assumptions of the synchronous PRAM model include the lock-step synchronicity of processors and the lack of collision on concurrent memory accesses to the same locations [9,10,18].…”
Section: Memory Modelmentioning
confidence: 99%
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