Recent developments in high-level synthesis
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Application-specific heterogeneous multiprocessor synthesis using differential-evolution
Proceedings of the 11th international symposium on System synthesis
Multiclock selection and synthesis for CDFGs using optimal clock sets and genetic algorithms
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Journal of Parallel and Distributed Computing - Problems in parallel and distributed computing: Solutions based on evolutionary paradigms
Heterogeneous Multiprocessor Scheduling and Allocation using Evolutionary Algorithms
ASAP '97 Proceedings of the IEEE International Conference on Application-Specific Systems, Architectures and Processors
An Enhanced Genetic Solution for Scheduling, Module Allocation, and Binding in VLSI Design
VLSID '97 Proceedings of the Tenth International Conference on VLSI Design: VLSI in Multimedia Applications
Co-evolutionary high-level test synthesis
Proceedings of the 17th ACM Great Lakes symposium on VLSI
A unified approach for scheduling and allocation
Integration, the VLSI Journal
Concurrent BIST synthesis and test scheduling using genetic algorithms
International Journal of Computers and Applications
Integrated design space exploration based on power-performance trade-off using genetic algorithm
ACAI '11 Proceedings of the International Conference on Advances in Computing and Artificial Intelligence
A systematic approach to classify design-time global scheduling techniques
ACM Computing Surveys (CSUR)
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This paper presents a new approach to datapath synthesis based on a problem-space genetic algorithm (PSGA). The proposed technique performs concurrent scheduling and allocation of functional units, registers, and multiplexers with the objective of finding both a schedule and an allocation which minimizes the cost function of the hardware resources and the total time of execution. The problem-space genetic algorithm based datapath synthesis system (PSGA-Synth) combines a standard genetic algorithm with a known heuristic to search the large design space in an intelligent manner. PSGA-Synth handles multicycle functional units, structural pipelining, conditional code and loops, and provides a mechanism to specify lower and upper bounds on the number of control steps. The PSGA-Synth was tested on a set of problems selected from the literature, as well as larger problems created by us, with promising results. PSGA-Synth not only finds the best known results for all the test problems examined in a relatively small amount of CPU time, but also has the ability to efficiently handle large problems