Adaptive granularity memory systems: A tradeoff between storage efficiency and throughput

D. Yoon, Minseong Jeong, M. Erez
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引用次数: 92

Abstract

We propose adaptive granularity to combine the best of fine-grained and coarse-grained memory accesses. We augment virtual memory to allow each page to specify its preferred granularity of access based on spatial locality and error-tolerance tradeoffs. We use sector caches and sub-ranked memory systems to implement adaptive granularity. We also show how to incorporate adaptive granularity into memory access scheduling. We evaluate our architecture with and without ECC using memory intensive benchmarks from the SPEC, Olden, PARSEC, SPLASH2, and HPCS benchmark suites and micro-benchmarks. The evaluation shows that performance is improved by 61% without ECC and 44% with ECC in memory-intensive applications, while the reduction in memory power consumption (29% without ECC and 14% with ECC) and traffic (78% without ECC and 66% with ECC) is significant.
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自适应粒度内存系统:存储效率和吞吐量之间的权衡
我们提出自适应粒度来结合细粒度和粗粒度的最佳内存访问。我们增加了虚拟内存,允许每个页面根据空间局域性和容错权衡来指定其首选的访问粒度。我们使用扇区缓存和子分级内存系统来实现自适应粒度。我们还将展示如何将自适应粒度合并到内存访问调度中。我们使用SPEC、Olden、PARSEC、SPLASH2和HPCS基准套件和微基准测试中的内存密集型基准测试来评估有ECC和没有ECC的架构。评估表明,在内存密集型应用中,没有ECC的性能提高了61%,使用ECC的性能提高了44%,而内存功耗(没有ECC的为29%,使用ECC的为14%)和流量(没有ECC的为78%,使用ECC的为66%)的降低是显著的。
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