Phase-Based Data Placement Scheme for Heterogeneous Memory Systems

M. Laghari, Najeeb Ahmad, D. Unat
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引用次数: 6

Abstract

Heterogeneous memory systems are equipped with two or more types of memories, which work in tandem to complement the capabilities of each other. The multiple memories can vary in latency, bandwidth and capacity characteristics across systems and they come in various configurations that can be managed by the programmer. This introduces an added programming complexity for the programmer. In this paper, we present a dynamic phase-based data placement scheme to assist the programmer in making decisions about program object allocations. We devise a cost model to assess the benefit of having an object in one type of memory over the other and apply the cost model at every application phase to capture the dynamic behaviour of an application. Our cost model takes into account the reference counts of objects and incurred transfer overhead when making a suggestion. In addition, objects can be transferred across memories asynchronously between phases to mask some of the transfer overhead. We test our cost model with a diverse set of applications from NAS Parallel and Rodinia benchmarks and perform experiments on Intel KNL, which is equipped with a high bandwidth memory (MCDRAM) and a high capacity memory (DDR). Our dynamic phase-based data placement performs better than initial placement and achieves comparable or better performance than cache mode of MCDRAM.
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异构存储系统中基于相位的数据放置方案
异构存储器系统配备了两种或两种以上类型的存储器,它们串联工作以补充彼此的能力。多个存储器在不同系统的延迟、带宽和容量特性上可能有所不同,并且它们有不同的配置,可以由程序员管理。这给程序员带来了额外的编程复杂性。在本文中,我们提出了一个动态的基于阶段的数据放置方案,以帮助程序员做出关于程序对象分配的决策。我们设计了一个成本模型来评估在一种类型的内存中拥有对象比在另一种类型的内存中拥有对象的好处,并在每个应用程序阶段应用成本模型来捕获应用程序的动态行为。我们的成本模型在提出建议时考虑了对象的引用计数和产生的传输开销。此外,对象可以在各个阶段之间异步地跨内存传输,以掩盖一些传输开销。我们使用NAS Parallel和Rodinia基准测试的各种应用程序来测试我们的成本模型,并在配备高带宽内存(MCDRAM)和高容量内存(DDR)的Intel KNL上进行实验。我们的基于动态相位的数据放置性能优于初始放置,并达到与MCDRAM缓存模式相当或更好的性能。
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