Controlling the data space of tree structured computations

We study the problem of scheduling a parallel computation so as to minimize the maximum number of data items extant at any point in the execution. Computations are expressed as directed graphs, where nodes represent primitive operations and arcs represent data dependences. The result of an operation...

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Bibliographic Details
Published in:	Information and computation Vol. 187; no. 2; pp. 246 - 276
Main Authors:	Gottlieb, I., Obrenić, B.
Format:	Journal Article
Language:	English
Published:	San Diego, CA Elsevier Inc 15.12.2003 Elsevier
Subjects:	Applied sciences Computer science; control theory; systems Data processing. List processing. Character string processing Dataflow Exact sciences and technology Memory organisation. Data processing Multiprocessor scheduling algorithm Operational research and scientific management Operational research. Management science Precedence graph Precedence tree Scheduling, sequencing Software Token space Precedence graph Token space Precedence tree Dataflow Multiprocessor scheduling algorithm Processor Complete Constant Size Time Precedence constraint Data flow Result Multiprocessor Maximum Primitive Number Dependence Example Space Lower bound Optimal algorithm Complete graph Graph node Data space Data Scheduling Tree structure Algorithm Completion Graph Binary tree Schedule NP complete problem Parallel computation Problem Directed graph
ISSN:	0890-5401, 1090-2651
Online Access:	Get full text
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