Chen Zhong, Prajwal Challa, Xingsheng Zhao, Song Jiang
{"title":"Buffered Hash Table: Leveraging DRAM to Enhance Hash Indexes in the Persistent Memory","authors":"Chen Zhong, Prajwal Challa, Xingsheng Zhao, Song Jiang","doi":"10.1109/NVMSA56066.2022.00011","DOIUrl":null,"url":null,"abstract":"As a high-speed byte-addressable storage media similar to DRAM, Intel Optane DC Persistent Memory (PMem) has drawn the interest from the research community for its high throughput and low latency. These properties propel the migration of in-DRAM data structures, such as hash tables, to the PMem. However, existing PMem hash table designs do not recognize that the PMem is also a block device with an access unit of 256 bytes. Consequently, they carry out writes in sizes that are an order of magnitude smaller than the PMem access unit, leading to high write amplification. To improve their performance, we propose Buffered Hash Table (BHT) design. BHT batches multiple writes into in-DRAM buffers and then merges them into hash table buckets in the PMem, reducing the number of small writes. BHT also employs a PMem-based writeahead log to prevent data loss. Our experiments show that BHT provides up to 2.3X and 2.8X higher write throughput, assuming the DRAM space is sufficiently available, compared to the stateof-the-art hash indexes, namely CCEH and Dash, respectively.","PeriodicalId":185204,"journal":{"name":"2022 IEEE 11th Non-Volatile Memory Systems and Applications Symposium (NVMSA)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 11th Non-Volatile Memory Systems and Applications Symposium (NVMSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NVMSA56066.2022.00011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
As a high-speed byte-addressable storage media similar to DRAM, Intel Optane DC Persistent Memory (PMem) has drawn the interest from the research community for its high throughput and low latency. These properties propel the migration of in-DRAM data structures, such as hash tables, to the PMem. However, existing PMem hash table designs do not recognize that the PMem is also a block device with an access unit of 256 bytes. Consequently, they carry out writes in sizes that are an order of magnitude smaller than the PMem access unit, leading to high write amplification. To improve their performance, we propose Buffered Hash Table (BHT) design. BHT batches multiple writes into in-DRAM buffers and then merges them into hash table buckets in the PMem, reducing the number of small writes. BHT also employs a PMem-based writeahead log to prevent data loss. Our experiments show that BHT provides up to 2.3X and 2.8X higher write throughput, assuming the DRAM space is sufficiently available, compared to the stateof-the-art hash indexes, namely CCEH and Dash, respectively.
作为一种类似于DRAM的高速字节可寻址存储介质,英特尔Optane DC Persistent Memory (PMem)因其高吞吐量和低延迟而引起了研究社区的兴趣。这些特性推动了dram内数据结构(如哈希表)向PMem的迁移。然而,现有的PMem哈希表设计不承认PMem也是一个具有256字节访问单元的块设备。因此,它们执行的写操作的大小比PMem访问单元小一个数量级,从而实现高写放大。为了提高它们的性能,我们提出了缓冲哈希表(BHT)设计。BHT将多个写操作批处理到dram缓冲区中,然后将它们合并到PMem中的哈希表桶中,从而减少小写操作的数量。BHT还使用基于pmems的预写日志来防止数据丢失。我们的实验表明,与最先进的散列索引(即CCEH和Dash)相比,在假设DRAM空间足够可用的情况下,BHT提供了高达2.3倍和2.8倍的写吞吐量。