Proceedings of the 27th annual international symposium on Computer architecture
Interconnect characteristics of 2.5-D system integration scheme
Proceedings of the 2001 international symposium on Physical design
The V-Way Cache: Demand Based Associativity via Global Replacement
Proceedings of the 32nd annual international symposium on Computer Architecture
Die Stacking (3D) Microarchitecture
Proceedings of the 39th Annual IEEE/ACM International Symposium on Microarchitecture
Extending the effectiveness of 3D-stacked DRAM caches with an adaptive multi-queue policy
Proceedings of the 42nd Annual IEEE/ACM International Symposium on Microarchitecture
Thread Cluster Memory Scheduling: Exploiting Differences in Memory Access Behavior
MICRO '43 Proceedings of the 2010 43rd Annual IEEE/ACM International Symposium on Microarchitecture
IBM Journal of Research and Development
Efficiently enabling conventional block sizes for very large die-stacked DRAM caches
Proceedings of the 44th Annual IEEE/ACM International Symposium on Microarchitecture
MICRO-45 Proceedings of the 2012 45th Annual IEEE/ACM International Symposium on Microarchitecture
Adaptive cache management for a combined SRAM and DRAM cache hierarchy for multi-cores
Proceedings of the Conference on Design, Automation and Test in Europe
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Two key parameters that determine the performance of a DRAM cache based multi-core system are DRAM cache hit latency (HL) and DRAM cache miss rate (MR), as they strongly influence the average DRAM cache access latency. Recently proposed DRAM set mapping policies are either optimized for HL or for MR. None of these policies provides a good HL and MR at the same time. This paper presents a novel DRAM set mapping policy that simultaneously targets both parameters with the goal of achieving the best of both to reduce the overall DRAM cache access latency. For a 16-core system, our proposed set mapping policy reduces the average DRAM cache access latency (depends upon HL and MR) compared to state-of-the-art DRAM set mapping policies that are optimized for either HL or MR by 29.3% and 12.1%, respectively.