Optimal time and efficient space free scheduling for nested loops

Koziris, Nectarios; Papakonstantinou, George; Tsanakas, Panayotis

dc.contributor.author	Koziris, Nectarios	en
dc.contributor.author	Papakonstantinou, George	en
dc.contributor.author	Tsanakas, Panayotis	en
dc.date.accessioned	2014-03-01T01:12:10Z
dc.date.available	2014-03-01T01:12:10Z
dc.date.issued	1996	en
dc.identifier.issn	0010-4620	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/11987
dc.subject	Nested Loops	en
dc.subject.classification	Computer Science, Hardware & Architecture	en
dc.subject.classification	Computer Science, Information Systems	en
dc.subject.classification	Computer Science, Software Engineering	en
dc.subject.other	Computer software	en
dc.subject.other	Graph theory	en
dc.subject.other	Heuristic programming	en
dc.subject.other	Multiprocessing systems	en
dc.subject.other	PERT	en
dc.subject.other	Program compilers	en
dc.subject.other	Program processors	en
dc.subject.other	Scheduling	en
dc.subject.other	Nested loops	en
dc.subject.other	Sequential computer programs	en
dc.subject.other	Shared memory multiprocessor systems	en
dc.subject.other	Task graph scheduling techniques	en
dc.subject.other	Recursive functions	en
dc.title	Optimal time and efficient space free scheduling for nested loops	en
heal.type	journalArticle	en
heal.identifier.primary	10.1093/comjnl/39.5.439	en
heal.identifier.secondary	http://dx.doi.org/10.1093/comjnl/39.5.439	en
heal.language	English	en
heal.publicationDate	1996	en
heal.abstract	The most important issue when parallelizing sequential programs is the efficient assignment of computations into different processing elements. The most extensive, in terms of time execution, part of a program is the nested loops. Too many approaches have been devoted in parallelizing nested loops, and assigning the concurrent partitions of such a loop into different processors. In the past, all methods have been focused upon linear schedules produced by manipulating the reduced dependence graph, which in some cases achieve near optimal solutions. This paper presents a new method of free scheduling loop computations into time, based on task graph scheduling techniques. It will be shown that this schedule is optimal in terms of time, outperforming all linear schedules. Furthermore, in terms of total number of processors, the presented method includes a heuristic refinement of the free schedule which `shuffles' computations into time, without loss of the optimal time performance, to augment the mean processor utilization. In all cases, the proposed method uses less number of processors, while preserving the optimal total execution time. The `shuffling' of computations is based on graph theory approaches, and uses PERT problem techniques. Such scheduling is convenient for parallelizing tools (such as compilers), but has practical interest for shared memory multiprocessor systems, where the communication delay imposed by such non-regular scheduling is of no interest.	en
heal.publisher	Oxford Univ Press, Oxford, United Kingdom	en
heal.journalName	Computer Journal	en
dc.identifier.doi	10.1093/comjnl/39.5.439	en
dc.identifier.isi	ISI:A1996VW45000008	en
dc.identifier.volume	39	en
dc.identifier.issue	5	en
dc.identifier.spage	439	en
dc.identifier.epage	448	en