NDLI: Scans as primitive parallel operations

Content Provider	IEEE Xplore Digital Library
Author	Blelloch, G.E.
Copyright Year	1968
Abstract	A study of the effects of adding two scan primitives as unit-time primitives to PRAM (parallel random access machine) models is presented. It is shown that the primitives improve the asymptotic running time of many algorithms by an O(log n) factor, greatly simplifying the description of many algorithms, and are significantly easier to implement than memory references. It is argued that the algorithm designer should feel free to use these operations as if they were as cheap as a memory reference. The author describes five algorithms that clearly illustrate how the scan primitives can be used in algorithm design: a radix-sort algorithm, a quicksort algorithm, a minimum-spanning-tree algorithm, a line-drawing algorithm, and a merging algorithm. These all run on an EREW (exclusive read, exclusive write) PRAM with the addition of two scan primitives and are either simpler or more efficient than their pure PRAM counterparts. The scan primitives have been implemented in microcode on the Connection Machine system, are available in PARIS (the parallel instruction set of the machine).<>
Sponsorship	IEEE Computer Society Technical Committee on Distributed Process IEEE Computer Society Technical Committee on VLSI IEEE Technical Committee on Computer Architecture IEEE Computer Society
Starting Page	1526
Ending Page	1538
Page Count	13
File Size	1419959
File Format	PDF
ISSN	00189340
Volume Number	38
Issue Number	11
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1989-11-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Phase change random access memory Algorithm design and analysis Concurrent computing Hardware Artificial intelligence Merging Testing Sorting Parallel algorithms Read-write memory
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Computational Theory and Mathematics Software Hardware and Architecture

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