ProfDP: A Lightweight Profiler to Guide Data Placement in Heterogeneous Memory Systems
ProfDP: A Lightweight Profiler to Guide Data Placement in Heterogeneous Memory Systems
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ProfDP：指导异构内存系统中数据放置的轻量级分析器
DOI：
10.1145/3205289.3205320
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Xu Liu
中科院分区：
文献类型：
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作者：
Shasha Wen;L. Cherkasova;F. Lin;Xu Liu
新的内存技术，例如非易失性内存和堆栈内存，已经改革了现代和新兴计算机体系结构中的内存层次结构。不同类型的存储器集成到同一系统中变得很常见，称为异构存储器。通常，异构内存系统由一个小的快速组件和一个大的慢速组件组成。这鼓励了新的数据处理方式，并给开发人员带来了一个新问题：给定两种内存类型，我们如何重新设计应用程序以从这种内存安排中受益并决定有效的数据放置？现有方法执行详细的内存访问模式分析以指导数据放置。然而，这些方法都是重量级的，并且忽略了软件和硬件之间的交互。为了解决这些问题，我们开发了 ProfDP，这是一种轻量级分析器，它采用以差异数据为中心的分析，为异构内存中的数据放置提供直观的指导。通过在最先进的模拟器和具有异构内存的真实机器上运行的多个并行基准进行评估，我们表明 ProfDP 能够指导近乎最佳的数据放置，从而以最少的编程工作来最大化性能。
New memory technologies, such as non-volatile memory and stacked memory, have reformed the memory hierarchies in modern and emerging computer architectures. It becomes common to see memories of different types integrated into the same system, as known as heterogeneous memory. Typically, a heterogeneous memory system consists of a small fast component and a large slow component. This encourages new style of data processing and exposes developers with a new problem: given two memory types, how shall we redesign applications to benefit from this memory arrangement and decide on the efficient data placement? Existing methods perform detailed memory access pattern analysis to guide data placement. However, these methods are heavyweight and ignore the interactions between software and hardware. To address these issues, we develop ProfDP, a lightweight profiler that employs differential data-centric analysis to provide intuitive guidance for data placement in heterogeneous memory. Evaluated with a number of parallel benchmarks running on a state-of-the-art emulator and a real machine with heterogeneous memory, we show that ProfDP is able to guide nearly-optimal data placement to maximize performance with minimum programming efforts.