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Data-Driven Thread Execution on Heterogeneous Processors.

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Bibliographic Details
Title:	Data-Driven Thread Execution on Heterogeneous Processors.
Authors:	Arandi, Samer¹ arandi@najah.edu, Matheou, George² geomat@cs.ucy.ac.cy, Kyriacou, Costas³ eng.kc@frederick.ac.cy, Evripidou, Paraskevas² skevos@cs.ucy.ac.cy
Source:	International Journal of Parallel Programming. Apr2018, Vol. 46 Issue 2, p198-224. 27p.
Subjects:	Simultaneous multithreading processors, Heterogeneous computing, Virtual machine systems, Data flow computing, High performance computing
Abstract:	In this paper we report our experience in implementing and evaluating the Data-Driven Multithreading (DDM) model on a heterogeneous multi-core processor. DDM is a non-blocking multithreading model that decouples the synchronization from the computation portions of a program, allowing them to execute asynchronously in a dataflow manner. Thread dependencies are determined by the compiler/programmer while thread scheduling is done dynamically at runtime based on data availability. The target processor for this implementation is the Cell processor. We call this implementation the Data-Driven Multithreading Virtual Machine for the Cell processor (DDM-VMc). Thread scheduling is handled in software by the Power Processing Element core of the Cell while the Synergistic Processing Element cores execute the program threads. DDM-VMc virtualizes the parallel resources of the Cell, handles the heterogeneity of the cores, manages the Cell memory hierarchy efficiently and supports distributed execution across a cluster of Cell nodes. DDM-VMc has been implemented on a single Cell processor with six computation cores, as well as, on a four Cell processor cluster with 24 computation cores. We present an in-depth performance analysis of DDM-VMc, using a suite of standard computational benchmarks. The evaluation shows that DDM-VMc scales well and tolerates scheduling overheads, memory and communication latencies effectively. Furthermore, DDM-VMc compares favorably with other platforms targeting the Cell processor, such as, the CellSs and Sequoia. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source
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