Abstract
The Parallel.FX Task Parallel Library is the latest tool developed for multicore parallelism optimization using the .NET technology. It is a managed concurrency library that provides optimized managed code for multicore processors using a new thread pool that withstands cancellation, waiting and pool isolation, among many other features. The Task Parallel Library also uses dynamic work stealing techniques for superior scalability. This paper analyzes the performance improvement of using the Task Parallel Library of Parallel.FX when applying a Multi-Objective Evolutionary Algorithm to solve a timetabling problem. For comparative purposes, this algorithm has also been parallelized using threads. The results obtained show that both alternatives allow a reduction in the runtime necessary to solve this problem. However, parallelizing the code using the Task Parallel Library of Parallel.FX has the advantage of being easier and the code size is much smaller than directly programming threads.
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