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Strategies for concurrent processing of complex algorithms in data driven architecturesThe performance modeling and enhancement for periodic execution of large-grain, decision-free algorithms in data flow architectures is examined. Applications include real-time implementation of control and signal processing algorithms where performance is required to be highly predictable. The mapping of algorithms onto the specified class of data flow architectures is realized by a marked graph model called ATAMM (Algorithm To Architecture Mapping Model). Performance measures and bounds are established. Algorithm transformation techniques are identified for performance enhancement and reduction of resource (computing element) requirements. A systematic design procedure is described for generating operating conditions for predictable performance both with and without resource constraints. An ATAMM simulator is used to test and validate the performance prediction by the design procedure. Experiments on a three resource testbed provide verification of the ATAMM model and the design procedure.
Document ID
Document Type
Contractor Report (CR)
Stoughton, John W.
(Old Dominion Univ. Norfolk, VA, United States)
Mielke, Roland R.
(Old Dominion Univ. Norfolk, VA, United States)
Som, Sukhamony
(Old Dominion Univ. Norfolk, VA, United States)
Date Acquired
September 6, 2013
Publication Date
April 1, 1990
Subject Category
Computer Programming And Software
Report/Patent Number
NAS 1.26:186515
Accession Number
Funding Number(s)
Distribution Limits
Work of the US Gov. Public Use Permitted.
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