Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Scheduling DAG's for Asynchronous Multiprocessor Execution
IEEE Transactions on Parallel and Distributed Systems
Automatically partitioning packet processing applications for pipelined architectures
Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation
GA-Based Automated Task Assignment on Network Processors
ICPADS '05 Proceedings of the 11th International Conference on Parallel and Distributed Systems - Volume 01
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In several commercial network processors programming environments, programmer must manually assign many processing tasks to the processor pipelines which consist of many processing engines. Due to the large exploration space, this manual procedure is usually very tedious and inefficient and the optimal or even near-optimal assignment scheme may be difficult to obtain. This paper proposes an automated task-to-PE assignment algorithm based on genetic algorithm. Experimental results show that this method can quickly obtain near-optimal solutions from the large solution space and the algorithm execution time is decoupled with pipeline stages. These two features make this method very suitable to be used in a NP application development environment and provide a more efficient development experience for developers.