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Mapping task graphs onto Network Processors using genetic algorithm
Multi-Task Processing
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108 b
30 dni za vračilo blaga
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This book presents an automated task scheduling§technique to address this parallel programming§complexity. Our proposed technique is based on GA. By§incorporating tasks dependency into scheduling list§and encoding task scheduling list as a chromosome, GA§can quickly remove the invalid mappings and evolve to§the high quality solutions. This technique takes§advantage of task-level and application-level§parallelism to maximize system performance for a§given NPs architecture. The simulation results show§that this proposed technique can generate high§quality mapping comparing to other heuristics by§mapping some sample network applications. This work§will also enable researchers and engineers to§systematically evaluate and quantitatively understand§the NPs system issues including application§partitioning, architecture organizing, workload§mapping and run-time operating
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