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Towards Multicore Performance with Configurable Computing Units

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Architecture of Computing Systems – ARCS 2016 (ARCS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9637))

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Abstract

Energy efficiency and the need for high performance has steered computing platforms toward customization. General purpose computing however remains a challenge as on-chip resources continue to increase with a limited performance improvement. In order to truly improve processor performance, a major reconsideration at the microarchitectural level must be sought with regards to the compiler, ISA, and general architecture without an explicit dependence on transistor scaling and increased cache levels. In attempts to assign the processor transistor budget towards engineering ingenuity, this paper presents the concept of Configurable Computing Units (CCUs). CCUs are designed to make reconfigurability in general purpose computing a reality by introducing the concept of logical and physical compilation. This concept allows for both the application and underlying architecture to be considered during the compilation process. Experimental results demonstrate that a single CCU core (consisting of double engines) achieves dual core performance, with half the area and power consumption required of a conventional monolithic CPU.

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Acknowledgement

The authors of this work would like to acknowledge the support and funding provided by the Ontario Graduate Scholarship (OGS) program and Ryerson University FEAS.

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Correspondence to Anita Tino .

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© 2016 Springer International Publishing Switzerland

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Tino, A., Raahemifar, K. (2016). Towards Multicore Performance with Configurable Computing Units. In: Hannig, F., Cardoso, J.M.P., Pionteck, T., Fey, D., Schröder-Preikschat, W., Teich, J. (eds) Architecture of Computing Systems – ARCS 2016. ARCS 2016. Lecture Notes in Computer Science(), vol 9637. Springer, Cham. https://doi.org/10.1007/978-3-319-30695-7_1

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  • DOI: https://doi.org/10.1007/978-3-319-30695-7_1

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30694-0

  • Online ISBN: 978-3-319-30695-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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