High Performance Computing Applications Using Parallel Data Processing Units

Abstract : Multicore processors are growing with respect to the number of cores on a chip. In a parallel computation context, multicore platforms have several important features such as exploiting multiple parallel processes, having access to a shared memory with noticeably lower cost than the distributed alternative and optimizing different levels of parallelism. In this paper, we introduce the Parallel Data Processing Unit (PDPU) which is a group of objects that benefits from the shared memory of the multicore configuration and that consists of two parts: a shared memory for maintaining data consistent, and a set of objects that are processing the data, then producing and aggregating the results concurrently. We then implement two examples in Java that illustrate PDPU behavior, and compare them with their actor based counterparts and show significant performance improvements. We also put forward the idea of integrating PDPU with the actor model which will result in an optimization for a specific spectrum of problems in actor based development.
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Mehdi Dastani; Marjan Sirjani. 6th Fundamentals of Software Engineering (FSEN), Apr 2015, Tehran, Iran. Springer, Lecture Notes in Computer Science, LNCS-9392, pp.191-206, 2015, Fundamentals of Software Engineering. 〈10.1007/978-3-319-24644-4_13〉
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Keyvan Azadbakht, Vlad Serbanescu, Frank Boer. High Performance Computing Applications Using Parallel Data Processing Units. Mehdi Dastani; Marjan Sirjani. 6th Fundamentals of Software Engineering (FSEN), Apr 2015, Tehran, Iran. Springer, Lecture Notes in Computer Science, LNCS-9392, pp.191-206, 2015, Fundamentals of Software Engineering. 〈10.1007/978-3-319-24644-4_13〉. 〈hal-01446600〉

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