Abstract
In the paper we present parallel implementations as well as execution times and speed-ups of three different algorithms run in various environments such as on a workstation with multi-core CPUs and a cluster. The parallel codes, implementing the master-slave model in C+MPI, differ in computation to communication ratios. The considered problems include: a genetic algorithm with various ratios of master processing time to communication and fitness evaluation times, matrix multiplication and numerical integration. We present how the codes scale in the aforementioned systems. For the numerical integration code that scales very well we also show performance in a hybrid CPU+Xeon Phi environment.
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Krzywaniak, A., Czarnul, P. (2018). Parallelization of Selected Algorithms on Multi-core CPUs, a Cluster and in a Hybrid CPU+Xeon Phi Environment. In: Borzemski, L., Świątek, J., Wilimowska, Z. (eds) Information Systems Architecture and Technology: Proceedings of 38th International Conference on Information Systems Architecture and Technology – ISAT 2017. ISAT 2017. Advances in Intelligent Systems and Computing, vol 655. Springer, Cham. https://doi.org/10.1007/978-3-319-67220-5_27
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DOI: https://doi.org/10.1007/978-3-319-67220-5_27
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