Abstract

In the paper, we review a suboptimal methodology of mapping of a task information graph on the architecture of a reconfigurable computer system. Using performance reduction methods, we can solve computational problems which need hardware costs exceeding the available hardware resource. We proved theorems, concerning properties of sequential reductions. In our case, we have the following types of reduction such as the reduction by number of basic subgraphs, by number of computing devices, and by data width. On the base of the proved theorems and corollaries, we developed the methodology of reduction transformations of a task information graph for its automatic adaptation to the architecture of a reconfigurable computer system. We estimated the maximum number of transformations, which, according to the suggested methodology, are needed for balanced reduction of the performance and hardware costs of applications for reconfigurable computer systems.

Highlights

  • Most researchers of parallel computing [1,2,3,4] admit that parallel programming is a complex area

  • In the first section we describe the forms of parallel calculations, and the task information graph used for structural and procedural calculations on the reconfigurable computer systems (RCS)

  • If we reduce the performance in order to decrease the hardware costs, all types of reduction transformations are performed in a balanced manner

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Summary

Introduction

Most researchers of parallel computing [1,2,3,4] admit that parallel programming is a complex area. For certain problem domains [17, 18], RCSs are considerably superior in real performance and power efficiency in contrast with cluster MCSs. In the paper, we consider a theory which helps to reduce the number of variants parallel calculations for analysis and further synthesis of a computing structure for an RCS. It is possible to synthesize computing structures and to increase the task solution time owing to the performance reduction methods. In this case, the efficiency of the designed structures is not less than 50 % in comparison with those designed by circuit engineers. In the conclusion we generalize our results and discuss the directions of our future research

Forms of Calculations
Mapping of Information Graphs on Reconfigurable Computer Systems
Methods of Performance and Hardware Costs Reduction
Order of Reduction Transformations For Synthesis of Computing Structures
Findings
Conclusion
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