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Trends in Microfabrication Capabilities & Device Architectures

Bauer, Todd B.; Jones, Adam J.; Lentine, Anthony L.; Mudrick, John M.; Okandan, Murat; Rodrigues, Arun

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Design methodology for optimizing optical interconnection networks in high performance systems

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Rumley, Sebastien; Glick, Madeleine; Hammond, Simon D.; Rodrigues, Arun; Bergman, Keren

Modern high performance computers connect hundreds of thousands of endpoints and employ thousands of switches. This allows for a great deal of freedom in the design of the network topology. At the same time, due to the sheer numbers and complexity involved, it becomes more challenging to easily distinguish between promising and improper designs. With ever increasing line rates and advances in optical interconnects, there is a need for renewed design methodologies that comprehensively capture the requirements and expose tradeoffs expeditiously in this complex design space. We introduce a systematic approach, based on Generalized Moore Graphs, allowing one to quickly gauge the ideal level of connectivity required for a given number of end-points and traffic hypothesis, and to collect insight on the role of the switch radix in the topology cost. Based on this approach, we present a methodology for the identification of Pareto-optimal topologies. We apply our method to a practical case with 25,000 nodes and present the results.

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Using a complementary emulation-simulation co-design approach to assess application readiness for Processing-in-Memory systems

Proceedings of Co-HPC 2014: 1st International Workshop on Hardware-Software Co-Design for High Performance Computing - Held in Conjunction with SC 2014: The International Conference for High Performance Computing, Networking, Storage and Analysis

Stelle, George; Olivier, Stephen L.; Stark, Dylan S.; Rodrigues, Arun; Hemmert, Karl S.

Disruptive changes to computer architecture are paving the way toward extreme scale computing. The co-design strategy of collaborative research and development among computer architects, system software designers, and application teams can help to ensure that applications not only cope but thrive with these changes. In this paper, we present a novel combined co-design approach of emulation and simulation in the context of investigating future Processing in Memory (PIM) architectures. PIM enables co-location of data and computation to decrease data movement, to provide increases in memory speed and capacity compared to existing technologies and, perhaps most importantly for extreme scale, to improve energy efficiency. Our evaluation of PIM focuses on three mini-applications representing important production applications. The emulation and simulation studies examine the effects of locality-aware versus locality-oblivious data distribution and computation, and they compare PIM to conventional architectures. Both studies contribute in their own way to the overall understanding of the application-architecture interactions, and our results suggest that PIM technology shows great potential for efficient computation without negatively impacting productivity.

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Results 51–75 of 118
Results 51–75 of 118