{"title":"hashh:用于混合ram - nvm内存的热点感知和可扩展动态哈希","authors":"Z. Li, Zhipeng Tan, Jianxi Chen","doi":"10.1109/ICCD53106.2021.00034","DOIUrl":null,"url":null,"abstract":"Intel Optane DC Persistent Memory Module (DCPMM) is the first commercially available non-volatile memory (NVM) product and can be directly placed on the processor’s memory bus along with DRAM to serve as a hybrid memory. Compared with DRAM, NVM has 3× read latency and similar write latency, while the read and write bandwidths of NVM are only 1/3rd and 1/6th of those of DRAM. However, existing hashing schemes fail to reap those performance characteristics. We propose HASDH, a hotspot-aware and scalable dynamic hashing built on the hybrid DRAM-NVM memory. HASDH maintains structure metadata (i.e., directory) in DRAM and persists key-value items in NVM. To reduce hot key-value items’ access cost, HASDH caches frequently-accessed key-value items in DRAM with a dedicated caching strategy. To achieve scalable performance for multicore machines, HASDH maintains locks in DRAM that avoid the extra NVM read-write bandwidth consumption caused by lock operations. Furthermore, HASDH chains all NVM segments using sibling pointers to the right neighbors to ensure crash consistency and leverages log-free NVM segment split to reduce logging overhead. On an 18-core machine with Intel Optane DCPMM, experimental results show that HASDH achieves 1.43∼7.39× speedup for insertions, 2.08~9.63× speedup for searches, and 1.78~3.01× speedup for deletions, compared with start-of-the-art NVM-based hashing indexes.","PeriodicalId":154014,"journal":{"name":"2021 IEEE 39th International Conference on Computer Design (ICCD)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"HASDH: A Hotspot-Aware and Scalable Dynamic Hashing for Hybrid DRAM-NVM Memory\",\"authors\":\"Z. Li, Zhipeng Tan, Jianxi Chen\",\"doi\":\"10.1109/ICCD53106.2021.00034\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Intel Optane DC Persistent Memory Module (DCPMM) is the first commercially available non-volatile memory (NVM) product and can be directly placed on the processor’s memory bus along with DRAM to serve as a hybrid memory. Compared with DRAM, NVM has 3× read latency and similar write latency, while the read and write bandwidths of NVM are only 1/3rd and 1/6th of those of DRAM. However, existing hashing schemes fail to reap those performance characteristics. We propose HASDH, a hotspot-aware and scalable dynamic hashing built on the hybrid DRAM-NVM memory. HASDH maintains structure metadata (i.e., directory) in DRAM and persists key-value items in NVM. To reduce hot key-value items’ access cost, HASDH caches frequently-accessed key-value items in DRAM with a dedicated caching strategy. To achieve scalable performance for multicore machines, HASDH maintains locks in DRAM that avoid the extra NVM read-write bandwidth consumption caused by lock operations. Furthermore, HASDH chains all NVM segments using sibling pointers to the right neighbors to ensure crash consistency and leverages log-free NVM segment split to reduce logging overhead. On an 18-core machine with Intel Optane DCPMM, experimental results show that HASDH achieves 1.43∼7.39× speedup for insertions, 2.08~9.63× speedup for searches, and 1.78~3.01× speedup for deletions, compared with start-of-the-art NVM-based hashing indexes.\",\"PeriodicalId\":154014,\"journal\":{\"name\":\"2021 IEEE 39th International Conference on Computer Design (ICCD)\",\"volume\":\"56 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 39th International Conference on Computer Design (ICCD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCD53106.2021.00034\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 39th International Conference on Computer Design (ICCD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCD53106.2021.00034","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
摘要
英特尔Optane DC Persistent Memory Module (DCPMM)是第一款商用非易失性内存(NVM)产品,可以直接与DRAM一起放置在处理器的内存总线上,作为混合内存。与DRAM相比,NVM的读时延是DRAM的3倍,写时延也差不多,而读写带宽仅为DRAM的1/3和1/6。然而,现有的散列方案无法获得这些性能特征。我们提出了一种基于混合DRAM-NVM内存的热点感知和可扩展的动态哈希算法HASDH。HASDH在DRAM中维护结构元数据(即目录),并在NVM中持久化键值项。为了降低热键值项的访问成本,HASDH使用专用缓存策略将频繁访问的键值项缓存到DRAM中。为了实现多核机器的可扩展性能,HASDH在DRAM中维护锁,避免了锁操作造成的额外NVM读写带宽消耗。此外,HASDH使用兄弟指针将所有NVM段链接到正确的邻居,以确保崩溃一致性,并利用无日志的NVM段分割来减少日志开销。在使用Intel Optane DCPMM的18核机器上,实验结果表明,与基于nvm的初始哈希索引相比,HASDH在插入方面实现了1.43 ~ 7.39倍的加速,在搜索方面实现了2.08~9.63倍的加速,在删除方面实现了1.78~3.01倍的加速。
HASDH: A Hotspot-Aware and Scalable Dynamic Hashing for Hybrid DRAM-NVM Memory
Intel Optane DC Persistent Memory Module (DCPMM) is the first commercially available non-volatile memory (NVM) product and can be directly placed on the processor’s memory bus along with DRAM to serve as a hybrid memory. Compared with DRAM, NVM has 3× read latency and similar write latency, while the read and write bandwidths of NVM are only 1/3rd and 1/6th of those of DRAM. However, existing hashing schemes fail to reap those performance characteristics. We propose HASDH, a hotspot-aware and scalable dynamic hashing built on the hybrid DRAM-NVM memory. HASDH maintains structure metadata (i.e., directory) in DRAM and persists key-value items in NVM. To reduce hot key-value items’ access cost, HASDH caches frequently-accessed key-value items in DRAM with a dedicated caching strategy. To achieve scalable performance for multicore machines, HASDH maintains locks in DRAM that avoid the extra NVM read-write bandwidth consumption caused by lock operations. Furthermore, HASDH chains all NVM segments using sibling pointers to the right neighbors to ensure crash consistency and leverages log-free NVM segment split to reduce logging overhead. On an 18-core machine with Intel Optane DCPMM, experimental results show that HASDH achieves 1.43∼7.39× speedup for insertions, 2.08~9.63× speedup for searches, and 1.78~3.01× speedup for deletions, compared with start-of-the-art NVM-based hashing indexes.