Supporting Sequential Consistency through Ordered Network in Many-Core Systems

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Supporting Sequential Consistency through Ordered Network in Many-Core Systems

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2017-12

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Recently, there are two trends in parallel computing. On one hand, emerging workloads have exhibited significant data-level parallelism; on the other hand, modern processors are increasing in core count to satisfy the increasing demand of processing power under stringent power and thermal constraints. Hence, multi-core and many-core systems have become ubiquitous. To facilitate software development on such processors, it is desirable to efficiently support an intuitive memory consistency model, such as the sequential consistency model. In this work, we demonstrate the feasibility of supporting the sequential memory consistency model on many-core systems. Our experiments show that in many-core systems where in-order cores with no private caches and shared memory modules are connected with a 2D-mesh network that supports circuit-switching, we are able to efficiently support sequential memory consistency by ordering memory requests in the network. In this work, memory requests are ordered by time-stamping each memory request and circulating a token among the memory modules. Furthermore, we extended the mechanism for ordering memory traffic in network to speed-up the performance of critical sections. We evaluated the proposed techniques on three different many-core systems that contain 8, 20 and 32 cores respectively. Compared to conventional systems where sequential consistency is supported by serializing memory requests at the cores through fences, the proposed systems are able to outperform the conventional systems by 4.95% , 5.74% and 9.70% respectively on the three different many-core systems.

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University of Minnesota M.S.E.E. thesis.December 2017. Major: Computer Engineering. Advisor: Antonia Zhai. 1 computer file (PDF); vi, 48 pages.

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Venkataraman, Hariharasudhan. (2017). Supporting Sequential Consistency through Ordered Network in Many-Core Systems. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/194668.

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