NVM/DRAM hybrid memory management with language runtime support via MRW queue
NVM/DRAM hybrid memory management with language runtime support via MRW queue
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DOI：
10.1109/snpd.2015.7176226
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发表时间：
2015-06
期刊：
影响因子：
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通讯作者：
Gaku Nakagawa;S. Oikawa
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文献类型：
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作者：
Gaku Nakagawa;S. Oikawa
非易失性存储器(NVM)，如PCM、STTMRAM和ReRAM，使将辅助存储集成到主存储器中成为可能。这种集成减少了通常较慢的块设备的I/O访问时间；然而，此时使用单个NVM构建大容量主内存是不现实的，因为NVM在写访问方面存在缺点。有必要将NVM和其他存储设备结合起来，以掩盖这些缺点。特别是，我们应该将写热数据放在DRAM上，将冷写数据放在NVM上。对于数据放置，编程语言运行时支持非常有用，因为它们比操作系统具有更详细的写访问信息。以前的一项研究提出了一种使用运行时支持的编程语言来管理NVM/DRAM混合内存的方法，根据对每个对象的写访问次数来确定数据放置(即单独计数方法)；然而，这种方法存在两个问题，即内存效率和数据放置阈值的确定。最近写入(MRW)队列方法是区分写热数据和写冷数据的另一种方法。MRW队列管理对对象的写入访问频率。在这项研究中，我们讨论了个体计数方法存在的问题，并使用MRW排队法给出了解决方案。实验结果表明，MRW队列方法提高了存储效率，降低了个体计数方法的开销。
Non-volatile memory (NVM), such as PCM, STTMRAM, and ReRAM, makes it possible to integrate secondary storage into main memory. This integration reduces I/O access times to typically slow block devices; however, it is unrealistic to construct a large capacity main memory with a single NVM at this time, because NVM have disadvantages regarding write access. Combining NVM and other memory devices is necessary to hide such disadvantages. In particular, we should place writehot data on DRAM and write-cold data on NVM. For data placement, programming language runtime supports are useful, since they have more detailed information about write access than the operating system. A previous study proposed a method to manage NVM/DRAM hybrid memory with programming language runtime supports, determining data placement based on the number of write accesses to each object (i.e., the individual counting method); however, this approach has two problems, namely memory efficiency and determination of threshold values for data placements. The Most Recent Write (MRW) queue method is an alternative method to distinguish between write-hot data and write-cold data. MRW queue manages the frequency of write accesses to objects. In this study, we discuss the problems of the individual counting method and show solutions using the MRW queue approach. Results of our experimentation show that the MRW queue method improves memory efficiency and reduces overhead of the individual counting method.