Performance analysis of static constraint network partitioning algorithm using multithreads
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The multicore processors can have its processing capacity well used when the applications are implemented in parallel using multithread programming. So, problems which demand high performance capacity and high data quantity can be executed faster. This work presents a performance analyze of a static partitioning algorithm over applications modeled in constraint graphs, named Grouping-Sink [2], in different hardware and software platforms. The sequential algorithm was parallelized using multithreads. The experiments were done over constraint networks. The results show that the parallelization using multithreads can achieve speedups until 473.19, using Linux operating system, with high priority. Besides, the threads scheduling realized by the operating system and the hardware architecture characteristics can affect the execution time of a parallel application.