Introduction to the Special Section on USENIX ATC 2021

Abstract

This special section of the ACM Transactions on Storage presents some highlights from the storagerelated papers published in the USENIX Annual Technical Conference (ATC’21). Although ATC is a broad conference that covers all practical aspects of systems software, a large proportion of its papers have traditionally been related to storage in some way. ATC’21 has continued this trend. Out of 341 submissions, the authors tagged 121 (35%) with one or more topic labels of “Storage,” “File Systems,” or “Databases and Transactions.” The conference accepted 64 papers (19%), of which 21 (33%) were storage related. As conference co-chairs, we selected three storage papers to be highlighted in this special section. All three were expanded and retitled by their authors and re-reviewed in fast-track mode by several of their original ATC’21 reviewers. We summarize them here in no particular order. The first article is “RACE: One-sided RDMA-conscious Extendible Hashing” by Pengfei Zuo, Qihui Zhou, Jiazhao Sun, Liu Yang, Shuangwu Zhang, Yu Hua, James Cheng, Rongfeng He, and Huabing Yan (titled “One-sided RDMA-conscious Extendible Hashing for Disaggregated Memory” in ATC’21). RACE is a client-centric RDMA hash table designed for disaggregated memory running on low-power CPUs. RACE completely bypasses the remote CPU for all key-value store operations and allows the hash table to be resized without impacting the concurrent foreground traffic. The second article, “SmartFVM: A Fast, Flexible, and Scalable Hardware-based Virtualization for Commodity Storage Devices” (originally “A Fast and Flexible Hardware-based Virtualization Mechanism for Computational Storage Devices”) is by Dongup Kwon, Wonsik Lee, Dongryeong Kim, Junehyuk Boo, and Jangwoo Kim. This article introduces a practical and low-overhead solution to virtualize computational storage devices that uses an FPGA with direct access to an SSD through NVMe. SmartFVM uses hardware-assisted virtualization to remove software-stack overheads while still maintaining isolation, and a hardware-level orchestration mechanism between the FPGA and the SSD. The final article is “Power Optimized Deployment of Key-value Stores Using Storage Class Memory” by Hiwot Tadese Kassa, Jason Akers, Mrinmoy Ghosh, Zhichao Cao, Vaibhav Gogte, and Ronald Dreslinski (previously “Improving Performance of Flash-based Key-value Stores Using Storage Class Memory as a Volatile Memory Extension”). It optimizes RocksDB by introducing a second layer of block cache using storage class memory. The article shows that adding storageclass memory to a smaller, single-socket server results in significant performance improvements for RocksDB in production deployments at Facebook, while improving the cost compared to large two-socket servers with DRAM only.