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Exploiting Program Semantics to Place Data in Hybrid Memory

Wei Wei ; Dejun Jiang ; Sally A McKee (Institutionen för data- och informationsteknik (Chalmers)) ; Jin Xiong ; Mingyu Chen
ACM/IEEE/IFIP International Conference on Parallel Architectures and Compilation Techniques (1089-795X). p. 163-173. (2015)
[Konferensbidrag, refereegranskat]

Large-memory applications like data analytics and graph processing benefit from extended memory hierarchies, and hybrid DRAM/NVM (non-volatile memory) systems represent an attractive means by which to increase capacity at reasonable performance/energy tradeoffs. Compared to DRAM, NVMs generally have longer latencies and higher energies for writes, which makes careful data placement essential for efficient system operation. Data placement strategies that resort to monitoring all data accesses and migrating objects to dynamically adjust data locations incur high monitoring overhead and unnecessary memory copies due to mispredicted migrations. We find that program semantics (specifically, global access characteristics) can effectively guide initial data placement with respect to memory types, which, in turn, makes run-time migration more efficient. We study a combined offline/online placement scheme that uses access profiling information to place objects statically and then selectively monitors run-time behaviors to optimize placements dynamically. We present a software/hardware cooperative framework, 2PP, and evaluate it with respect to state-of-the-art migratory placement, finding that it improves performance by an average of 12.1%. Furthermore, 2PP improves energy efficiency by up to 51.8%, and by an average of 18.4%. It does so by reducing run-time monitoring and migration overheads.

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Denna post skapades 2016-03-04. Senast ändrad 2016-08-23.
CPL Pubid: 232799


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