A parallel computing engine for a class of time critical processes

This paper focuses on the efficient parallel implementation of systems of numerically intensive nature over loosely coupled multiprocessor architectures. These analytical models are of significant importance to many real-time systems that have to meet severe time constants. A parallel computing engi...

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Vydané v:IEEE transactions on systems, man and cybernetics. Part B, Cybernetics Ročník 27; číslo 5; s. 774 - 786
Hlavní autori: Nabhan, T.M., Zomaya, A.Y.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States IEEE 01.10.1997
Predmet:
Analytical models
Computer architecture
Concurrent computing
Differential equations
Engines
Iterative algorithms
Numerical models
Optimal scheduling
Parallel processing
Real time systems
ISSN:1083-4419, 1941-0492
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Shrnutí:This paper focuses on the efficient parallel implementation of systems of numerically intensive nature over loosely coupled multiprocessor architectures. These analytical models are of significant importance to many real-time systems that have to meet severe time constants. A parallel computing engine (PCE) has been developed in this work for the efficient simplification and the near optimal scheduling of numerical models over the different cooperating processors of the parallel computer. First, the analytical system is efficiently coded in its general form. The model is then simplified by using any available information (e.g., constant parameters). A task graph representing the interconnections among the different components (or equations) is generated. The graph can then be compressed to control the computation/communication requirements. The task scheduler employs a graph-based iterative scheme, based on the simulated annealing algorithm, to map the vertices of the task graph onto a Multiple-Instruction-stream Multiple-Data-stream (MIMD) type of architecture. The algorithm uses a nonanalytical cost function that properly considers the computation capability of the processors, the network topology, the communication time, and congestion possibilities. Moreover, the proposed technique is simple, flexible, and computationally viable. The efficiency of the algorithm is demonstrated by two case studies with good results.
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ISSN:1083-4419
1941-0492
DOI:10.1109/3477.623231