Optimum and heuristic synthesis of multiple word-length architectures

This paper explores the problem of architectural synthesis (scheduling, allocation, and binding) for multiple word-length systems. It is demonstrated that the resource allocation and binding problem, and the interaction between scheduling, allocation, and binding, are complicated by the existence of...

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Bibliographic Details
Published in:IEEE transactions on very large scale integration (VLSI) systems 2005-01, Vol.13 (1), p.39-57
Main Authors: Constantinides, G.A., Cheung, P.Y.K., Luk, W.
Format: Article
Language:English
Subjects:
Allocations
Applied sciences
Binding
bitwidth
Circuit properties
Delay
Design. Technologies. Operation analysis. Testing
Digital circuits
Digital signal processing
Electric, optical and optoelectronic circuits
Electronic circuits
Electronics
Exact sciences and technology
Field programmable gate arrays
field-programmable gate array
Heuristic
High level synthesis
Information analysis
Integrated circuits
Integrated circuits by function (including memories and processors)
Mathematical models
Optimization
Performance analysis
Resource management
Scheduling
Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices
Signal processing algorithms
Synthesis
Time invariant systems
Very large scale integration
word-length
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Summary:This paper explores the problem of architectural synthesis (scheduling, allocation, and binding) for multiple word-length systems. It is demonstrated that the resource allocation and binding problem, and the interaction between scheduling, allocation, and binding, are complicated by the existence of multiple word-length operators. Both optimum and heuristic approaches to the combined problem are formulated. The optimum solution involves modeling as an integer linear program, while the heuristic solution considers intertwined scheduling, binding, and resource word-length selection. Techniques are introduced to perform scheduling with incomplete word-length information, to combine binding and word-length selection, and to refine word-length information based on critical path analysis. Results are presented for several benchmark and artificial examples, demonstrating significant resource savings of up to 46% are possible by considering these problems within the proposed unified framework.
ISSN:1063-8210
1557-9999
DOI:10.1109/TVLSI.2004.840398