An efficient algorithm for the physical mapping of clustered task graphs onto multiprocessor architectures

Koziris, N; Romesis, M; Tsanakas, P; Papakonstantinou, G

dc.contributor.author	Koziris, N	en
dc.contributor.author	Romesis, M	en
dc.contributor.author	Tsanakas, P	en
dc.contributor.author	Papakonstantinou, G	en
dc.date.accessioned	2014-03-01T02:48:56Z
dc.date.available	2014-03-01T02:48:56Z
dc.date.issued	2000	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/34131
dc.subject	Distributed Architecture	en
dc.subject	Efficient Algorithm	en
dc.subject	Low Complexity	en
dc.subject	Multiprocessor Architecture	en
dc.subject	Parallel Architecture	en
dc.subject	Parallel Programs	en
dc.subject	Physical Map	en
dc.subject	Precedence Constraint	en
dc.subject	Simulated Annealing	en
dc.subject	Task Graphs	en
dc.subject	Processing Element	en
dc.title	An efficient algorithm for the physical mapping of clustered task graphs onto multiprocessor architectures	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/EMPDP.2000.823437	en
heal.identifier.secondary	http://dx.doi.org/10.1109/EMPDP.2000.823437	en
heal.publicationDate	2000	en
heal.abstract	The most important issue in sequential program parallelisation is the efficient assignment of computations into different processing elements. In the past, too many approaches were devoted in efficient program parallelization considering various models for the parallel programs and the target architectures. The most widely used parallelism description model is the task graph model with precedence constraints. Nevertheless, as far as	en
heal.journalName	International Conference on Energy Management and Power Delivery	en
dc.identifier.doi	10.1109/EMPDP.2000.823437	en