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LosPem
ACM Journal on Emerging Technologies in Computing Systems ( IF 2.2 ) Pub Date : 2020-05-25 , DOI: 10.1145/3379932
Sumin Li 1 , Linpeng Huang 1
Affiliation  

New and emerging types of Persistent Memory (PM) technologies boost the opportunity to improve the performance of storage systems. PM can unify the main memory and secondary storage by incorporating it into legacy computer systems through the memory bus. In recent years, innovative results have been presented that exploit the byte-addressability, low latency, and non-volatility of PM; these have included local PM file systems and PM systems. However, the high overhead of ensuring data consistency has limited the performance of these systems. In this article, we propose LosPem, a novel log-structured framework for persistent memory to address the performance challenge. LosPem utilizes two techniques to accomplish this. Firstly, LosPem deploys efficient hash-indexed linked lists to maintain the log contents to reduce the significant overhead of log content retrieval. Secondly, LosPem improves the transaction throughput by decoupling a transaction into two asynchronous steps and creating a write buffer on Dynamic Random Access Memory (DRAM) write buffer for processing the frequent data writes. The experimental results show that LosPem outperforms Non-volatile Memory Library (NVML), Mnemosyne and Log-structured Non-volatile Main Memory (LSNVMM) by 27%, 1.2x, and 1.0x on a read-intensive workload. On a write-intensive workload, LosPem outperforms NVML, Mnemosyne, and LSNVMM by 1.8x, 1.2x, and 34%, respectively.

中文翻译:

洛斯佩姆

新兴类型的持久性内存 (PM) 技术增加了提高存储系统性能的机会。PM 可以通过内存总线将主存和辅助存储合并到遗留计算机系统中来统一主存和辅助存储。近年来,利用 PM 的字节寻址能力、低延迟和非易失性的创新成果已经出现;这些包括本地 PM 文件系统和 PM 系统。然而,确保数据一致性的高开销限制了这些系统的性能。在本文中,我们提出了 LosPem,这是一种用于持久内存的新型日志结构框架,以解决性能挑战。LosPem 利用两种技术来实现这一点。第一,LosPem 部署高效的哈希索引链表来维护日志内容,以减少日志内容检索的显着开销。其次,LosPem 通过将事务解耦为两个异步步骤并在动态随机存取存储器 (DRAM) 写缓冲区上创建一个写缓冲区来处理频繁的数据写入,从而提高了事务吞吐量。实验结果表明,在读取密集型工作负载上,LosPem 的性能比非易失性内存库 (NVML)、Mnemosyne 和日志结构非易失性主内存 (LSNVMM) 高 27%、1.2 倍和 1.0 倍。在写入密集型工作负载上,LosPem 的性能分别比 NVML、Mnemosyne 和 LSNVMM 高 1.8 倍、1.2 倍和 34%。LosPem 通过将事务解耦为两个异步步骤并在动态随机存取存储器 (DRAM) 写缓冲区上创建一个写缓冲区来处理频繁的数据写入,从而提高了事务吞吐量。实验结果表明,在读取密集型工作负载上,LosPem 的性能比非易失性内存库 (NVML)、Mnemosyne 和日志结构非易失性主内存 (LSNVMM) 高 27%、1.2 倍和 1.0 倍。在写入密集型工作负载上,LosPem 的性能分别比 NVML、Mnemosyne 和 LSNVMM 高 1.8 倍、1.2 倍和 34%。LosPem 通过将事务解耦为两个异步步骤并在动态随机存取存储器 (DRAM) 写缓冲区上创建一个写缓冲区来处理频繁的数据写入,从而提高了事务吞吐量。实验结果表明,在读取密集型工作负载上,LosPem 的性能比非易失性内存库 (NVML)、Mnemosyne 和日志结构非易失性主内存 (LSNVMM) 高 27%、1.2 倍和 1.0 倍。在写入密集型工作负载上,LosPem 的性能分别比 NVML、Mnemosyne 和 LSNVMM 高 1.8 倍、1.2 倍和 34%。
更新日期:2020-05-25
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