Scheduling and allocation in high-level synthesis using genetic algorithm

dc.contributor.authorShahid Ali
dc.date1994
dc.date.accessioned2022-05-18T05:20:29Z
dc.date.available2022-05-18T05:20:29Z
dc.degree.departmentCollege of Computer Science and Engineering
dc.degree.grantorKing Fahad for Petrolem University
dc.description.abstractHigh-level Synthesis (HLS) is the process of automatically translating abstract behavioral models of digital systems to implementable hardware. Operation scheduling and hardware allocation are the two most important phases in the synthesis of circuits from behavioral specification. Scheduling and allocation can be formulated as an optimization problem. In this work a unique approach to scheduling and allocation problem using the genetic paradigm is described. The main contributions include: (1) a new chromosomal representation for scheduling and for two subproblems of allocation, and (2) two novel crossover operators to generate legal schedules. In addition the application of tabu search to scheduling and allocation is also implemented and studied. Both techniques have been tested on various benchmarks and results obtained for data-oriented control-data flow graphs (CDFGs) are compared with other implementations. A novel interconnect optimization technique using genetic algorithm is also realized.
dc.identifier.other5292
dc.identifier.urihttps://drepo.sdl.edu.sa/handle/20.500.14154/1805
dc.language.isoen
dc.publisherSaudi Digital Library
dc.thesis.levelMaster
dc.thesis.sourceKing Fahad for Petrolem University
dc.titleScheduling and allocation in high-level synthesis using genetic algorithm
dc.typeThesis
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