Paper Info
Title
Strategies for predictability in real-time data-flow architectures
Abstract
Consideration is given to the development of strategies for predictable performance in homogeneous multicomputer data-flow architectures operating in real-time. Algorithms are restricted to the class of large-grained, decision-free algorithms. The mapping of such algorithms onto the specified class of data-flow architectures is realized by a new marked graph model called ATAMM (algorithm to architecture mapping model). Algorithm performance and resource needs are determined for predictable periodic execution of algorithms, which is achieved by algorithm modification and input data injection control. Performance is gracefully degraded to adapt to decreasing numbers of resources. The realization of the ATAMM model on a VHSIC four processor testbed is described. A software design tool for prediction of performance and resource requirements is described and is used to evaluate the performance of a space surveillance algorithm
Year
DOI
Venue
1990
10.1109/REAL.1990.128752
RTSS
Keywords
Field
DocType
input data injection control,large-grained,real-time data-flow architectures,gracefully degraded,space surveillance algorithm,parallel architectures,vhsic four processor testbed,mapping,predictability,software tools,software design tool,algorithm to architecture mapping model,performance evaluation,decision-free algorithms,performance,real-time systems,process control,real time systems,algorithm design and analysis,software design,data flow,prediction algorithms,real time data,computational modeling,real time,computer architecture,application software
Marked graph,Software design,Algorithm design,Real-time data,Computer science,Testbed,Real-time computing,Process control,VHSIC,Application software,Distributed computing
Conference
Citations 
PageRank 
References 
2
0.42
3
Authors
3
Name
Order
Citations
PageRank
Sukhamoy Som130.83
Roland R. Mielke2226.81
John W. Stoughton330.83