skip to main content
research-article

Localized Validation Accelerates Distributed Transactions on Disaggregated Persistent Memory

Published:19 June 2023Publication History
Skip Abstract Section

Abstract

Persistent memory (PM) disaggregation significantly improves the resource utilization and failure isolation to build a scalable and cost-effective remote memory pool in modern data centers. However, due to offering limited computing power and overlooking the bandwidth and persistence properties of real PMs, existing distributed transaction schemes, which are designed for legacy DRAM-based monolithic servers, fail to efficiently work on the disaggregated PM. In this article, we propose FORD, a Fast One-sided RDMA-based Distributed transaction system for the new disaggregated PM architecture. FORD thoroughly leverages one-sided remote direct memory access to handle transactions for bypassing the remote CPU in the PM pool. To reduce the round trips, FORD batches the read and lock operations into one request to eliminate extra locking and validations for the read-write data. To accelerate the transaction commit, FORD updates all remote replicas in a single round trip with parallel undo logging and data visibility control. Moreover, considering the limited PM bandwidth, FORD enables the backup replicas to be read to alleviate the load on the primary replicas, thus improving the throughput. To efficiently guarantee the remote data persistency in the PM pool, FORD selectively flushes data to the backup replicas to mitigate the network overheads. Nevertheless, the original FORD wastes some validation round trips if the read-only data are not modified by other transactions. Hence, we further propose a localized validation scheme to transfer the validation operations for the read-only data from remote to local as much as possible to reduce the round trips. Experimental results demonstrate that FORD significantly improves the transaction throughput by up to 3× and decreases the latency by up to 87.4% compared with state-of-the-art systems.

REFERENCES

  1. [1] Aguilera Marcos K., Amit Nadav, Calciu Irina, Deguillard Xavier, Gandhi Jayneel, Novakovic Stanko, Ramanathan Arun, et al. 2018. Remote regions: A simple abstraction for remote memory. In Proceedings of the 2018 USENIX Annual Technical Conference (USENIX ATC’18). 775787.Google ScholarGoogle Scholar
  2. [2] Akinaga Hiroyuki and Shima Hisashi. 2010. Resistive random access memory (ReRAM) based on metal oxides. Proceedings of the IEEE 98, 12 (2010), 22372251.Google ScholarGoogle ScholarCross RefCross Ref
  3. [3] Amaro Emmanuel, Branner-Augmon Christopher, Luo Zhihong, Ousterhout Amy, Aguilera Marcos K., Panda Aurojit, Ratnasamy Sylvia, and Shenker Scott. 2020. Can far memory improve job throughput? In Proceedings of the 15th EuroSys Conference (EuroSys’20). ACM, New York, NY, Article 14, 16 pages.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. [4] Anderson Thomas E., Canini Marco, Kim Jongyul, Kostic Dejan, Kwon Youngjin, Peter Simon, Reda Waleed, Schuh Henry N., and Witchel Emmett. 2020. Assise: Performance and availability via client-local NVM in a Distributed File System. In Proceedings of the 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI’20). 10111027.Google ScholarGoogle Scholar
  5. [5] Apalkov Dmytro, Khvalkovskiy Alexey, Watts Steven, Nikitin Vladimir, Tang Xueti, Lottis Daniel, Moon Kiseok, et al. 2013. Spin-transfer torque magnetic random access memory (STT-MRAM). ACM Journal on Emerging Technologies in Computing Systems 9, 2 (2013), Article 13, 35 pages.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. [6] Bernstein Philip A. and Goodman Nathan. 1981. Concurrency control in distributed database systems. ACM Computing Surveys 13, 2 (June1981), 185221.Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. [7] Bhardwaj Ankit, Thornley Todd, Pawar Vinita, Achermann Reto, Zellweger Gerd, and Stutsman Ryan. 2022. Cache-coherent accelerators for persistent memory crash consistency. In Proceedings of the 14th ACM Workshop on Hot Topics in Storage and File Systems (HotStorage’22). ACM, New York, NY, 3744.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. [8] Brewer Eric. 2012. CAP twelve years later: How the “rules” have changed. Computer 45, 2 (2012), 2329.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. [9] Brewer Eric A.. 2000. Towards robust distributed systems. In Proceedings of the 19th Annual ACM Symposium on Principles of Distributed Computing (PODC’00), Vol. 7. 343477343502.Google ScholarGoogle Scholar
  10. [10] Cai Qingchao, Guo Wentian, Zhang Hao, Agrawal Divyakant, Chen Gang, Ooi Beng Chin, Tan Kian-Lee, Teo Yong Meng, and Wang Sheng. 2018. Efficient distributed memory management with RDMA and caching. Proceedings of the VLDB Endowment 11, 11 (2018), 16041617.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. [11] Calciu Irina, Imran M. Talha, Puddu Ivan, Kashyap Sanidhya, Maruf Hasan Al, Mutlu Onur, and Kolli Aasheesh. 2021. Rethinking software runtimes for disaggregated memory. In Proceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS’21). ACM, New York, NY, 7992.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. [12] Cao Zhichao, Dong Siying, Vemuri Sagar, and Du David H. C.. 2020. Characterizing, modeling, and benchmarking RocksDB key-value workloads at Facebook. In Proceedings of the 18th USENIX Conference on File and Storage Technologies (FAST’20). 209223.Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. [13] Chen Jiqiang, Chen Liang, Wang Sheng, Zhu Guoyun, Sun Yuanyuan, Liu Huan, and Li Feifei. 2020. HotRing: A hotspot-aware in-memory key-value store. In Proceedings of the 18th USENIX Conference on File and Storage Technologies (FAST’20). 239252.Google ScholarGoogle Scholar
  14. [14] Chen Yanzhe, Wei Xingda, Shi Jiaxin, Chen Rong, and Chen Haibo. 2016. Fast and general distributed transactions using RDMA and HTM. In Proceedings of the 11th European Conference on Computer Systems (EuroSys’16). ACM, New York, NY, Article 26, 17 pages.Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. [15] Consortium CXL. 2022. Compute Express Link™: The Breakthrough CPU-to-Device Interconnect. Retrieved February 2, 2023 from https://www.computeexpresslink.org.Google ScholarGoogle Scholar
  16. [16] Cooper Brian F., Silberstein Adam, Tam Erwin, Ramakrishnan Raghu, and Sears Russell. 2010. Benchmarking cloud serving systems with YCSB. In Proceedings of the 1st ACM Symposium on Cloud Computing (SoCC’10). ACM, New York, NY, 143154.Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. [17] Corporation Edgecore Networks. 2022. DCS800 Data Center Switch. Retrieved February 2, 2023 from https://www.edge-core.com/_upload/images/2022-051-DCS800_Wedge100BF-32X-R10-20220705.pdf.Google ScholarGoogle Scholar
  18. [18] Corporation Hewlett Packard. 2022. The Machine: A New Kind of Computer. Retrieved February 2, 2023 from https://www.hpl.hp.com/research/systems-research/themachine/.Google ScholarGoogle Scholar
  19. [19] Corporation Intel. 2022. Intel Reports Second-Quarter 2022 Financial Results. Retrieved February 2, 2023 from https://www.intc.com/news-events/press-releases/detail/1563/intel-reports-second-quarter-2022-financial-results.Google ScholarGoogle Scholar
  20. [20] Corporation Intel. 2022. Intel®Optane™Persistent Memory. Retrieved February 2, 2023 from https://www.intel.com/content/www/us/en/products/docs/memory-storage/optane-persistent-memory/overview.html.Google ScholarGoogle Scholar
  21. [21] Corporation Intel. 2022. Intel®Optane™Persistent Memory 200 Series (512GB PMEM Module). Retrieved February 2, 2023 from https://www.intel.com/content/www/us/en/products/sku/203880/intel-optane-persistent-memory-200-series-512gb-pmem-module/specifications.html.Google ScholarGoogle Scholar
  22. [22] Corporation Intel. 2022. Intel®Rack Scale Design (Intel®RSD). Retrieved February 2, 2023 from https://www.intel.com/content/www/us/en/architecture-and-technology/rack-scale-design-overview.html.Google ScholarGoogle Scholar
  23. [23] Corporation Nantero. 2022. Nantero’s NRAM®. Retrieved February 2, 2023 from https://www.nantero.com/technology/.Google ScholarGoogle Scholar
  24. [24] Corporation NVIDIA and Affiliates. 2021. NVIDIA CONNECTX-5. Retrieved February 2, 2023 from https://nvdam.widen.net/s/pkxbnmbgkh/networking-infiniband-datasheet-connectx-5-2069273.Google ScholarGoogle Scholar
  25. [25] Corporation NVIDIA and Affiliates. 2021. NVIDIA CONNECTX-7. Retrieved February 2, 2023 from https://nvdam.widen.net/s/m6pt7j5rlb/networking-datasheet-infiniband-connectx-7-ds---1779005.Google ScholarGoogle Scholar
  26. [26] Corporation NVIDIA and Affiliates. 2022. NVIDIA CONNECTX-6. Retrieved February 2, 2023 from https://nvdam.widen.net/s/5j7xtzqfxd/connectx-6-infiniband-datasheet-1987500-r2.Google ScholarGoogle Scholar
  27. [27] Council The Transaction Processing. 2022. TPC-C Benchmark. Retrieved February 2, 2023 from http://www.tpc.org/tpcc/.Google ScholarGoogle Scholar
  28. [28] Database Azure SQL. 2022. Use Read-Only Replicas to Offload Read-Only Query Workloads. Retrieved February 2, 2023 from https://docs.microsoft.com/en-us/azure/azure-sql/database/read-scale-out.Google ScholarGoogle Scholar
  29. [29] Douglas Chet. 2015. RDMA with PM: Software mechanisms for enabling persistent memory replication. In Proceedings of the 2015 Storage Developer Conference.Google ScholarGoogle Scholar
  30. [30] Dragojevic Aleksandar, Narayanan Dushyanth, Castro Miguel, and Hodson Orion. 2014. FaRM: Fast remote memory. In Proceedings of the 11th USENIX Symposium on Networked Systems Design and Implementation (NSDI’14). 401414.Google ScholarGoogle Scholar
  31. [31] Dragojevic Aleksandar, Narayanan Dushyanth, Nightingale Edmund B., Renzelmann Matthew, Shamis Alex, Badam Anirudh, and Castro Miguel. 2015. No compromises: Distributed transactions with consistency, availability, and performance. In Proceedings of the 25th Symposium on Operating Systems Principles (SOSP’15). ACM, New York, NY, 5470.Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. [32] Gao Peter Xiang, Narayan Akshay, Karandikar Sagar, Carreira Joao, Han Sangjin, Agarwal Rachit, Ratnasamy Sylvia, and Shenker Scott. 2016. Network requirements for resource disaggregation. In Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI’16). 249264.Google ScholarGoogle Scholar
  33. [33] Gilbert Seth and Lynch Nancy. 2002. Brewer’s conjecture and the feasibility of consistent, available, partition-tolerant web services. ACM SIGACT News 33, 2 (2002), 5159.Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. [34] Gray Cary and Cheriton David. 1989. Leases: An efficient fault-tolerant mechanism for distributed file cache consistency. ACM SIGOPS Operating Systems Review 23, 5 (1989), 202210.Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. [35] Grun Paul, Bates Stephen, and Davis Rob. 2018. Persistent memory over fabrics. In Proceedings of the 2018 Persistent Memory Summit.Google ScholarGoogle Scholar
  36. [36] Gu Juncheng, Lee Youngmoon, Zhang Yiwen, Chowdhury Mosharaf, and Shin Kang G.. 2017. Efficient memory disaggregation with Infiniswap. In Proceedings of the 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI’17). 649667.Google ScholarGoogle Scholar
  37. [37] Guerraoui Rachid, Murat Antoine, Picorel Javier, Xygkis Athanasios, Yan Huabing, and Zuo Pengfei. 2022. uKharon: A membership service for microsecond applications. In Proceedings of the 2022 USENIX Annual Technical Conference (USENIX ATC’22). 101120.Google ScholarGoogle Scholar
  38. [38] Guo Zhiyuan, Shan Yizhou, Luo Xuhao, Huang Yutong, and Zhang Yiying. 2022. Clio: A hardware-software co-designed disaggregated memory system. In Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS’22). ACM, New York, NY, 417433.Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. [39] Guo Zhihan, Wu Kan, Yan Cong, and Yu Xiangyao. 2021. Releasing locks as early as you can: Reducing contention of hotspots by violating two-phase locking. In Proceedings of the International Conference on Management of Data (SIGMOD’21). ACM, New York, NY, 658670.Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. [40] Hakkarinen Doug, Wu Panruo, and Chen Zizhong. 2015. Fail-stop failure algorithm-based fault tolerance for Cholesky decomposition. IEEE Transactions on Parallel and Distributed Systems 26, 5 (2015), 13231335. Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. [41] Ho Chi, Renesse Robbert van, Bickford Mark, and Dolev Danny. 2008. Nysiad: Practical protocol transformation to tolerate Byzantine failures. In Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation (NSDI’08). 175188.Google ScholarGoogle Scholar
  42. [42] Jiang Tianyang, Zhang Guangyan, Li Zhiyue, and Zheng Weimin. 2022. Aurogon: Taming aborts in all phases for distributed in-memory transactions. In Proceedings of the 20th USENIX Conference on File and Storage Technologies (FAST’22). 217232.Google ScholarGoogle Scholar
  43. [43] Jung Myoungsoo. 2022. Hello bytes, bye blocks: PCIe storage meets Computer Express Link for memory expansion (CXL-SSD). In Proceedings of the 14th ACM Workshop on Hot Topics in Storage and File Systems (HotStorage’22). ACM, New York, NY, 4551.Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. [44] Kalia Anuj, Andersen David G., and Kaminsky Michael. 2020. Challenges and solutions for fast remote persistent memory access. In Proceedings of the ACM Symposium on Cloud Computing (SoCC’20). ACM, New York, NY, 105119.Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. [45] Kalia Anuj, Kaminsky Michael, and Andersen David G.. 2016. Design guidelines for high performance RDMA systems. In Proceedings of the 2016 USENIX Annual Technical Conference (USENIX’16). 437450.Google ScholarGoogle Scholar
  46. [46] Kalia Anuj, Kaminsky Michael, and Andersen David G.. 2016. FaSST: Fast, scalable and simple distributed transactions with two-sided (RDMA) datagram RPCs. In Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI’16). 185201.Google ScholarGoogle Scholar
  47. [47] Katsarakis Antonios, Ma Yijun, Tan Zhaowei, Bainbridge Andrew, Balkwill Matthew, Dragojevic Aleksandar, Grot Boris, Radunovic Bozidar, and Zhang Yongguang. 2021. Zeus: Locality-aware distributed transactions. In Proceedings of the 16th European Conference on Computer Systems (EuroSys’21). ACM, New York, NY, 145161.Google ScholarGoogle ScholarDigital LibraryDigital Library
  48. [48] Kim Daehyeok, Memaripour Amirsaman, Badam Anirudh, Zhu Yibo, Liu Hongqiang Harry, Padhye Jitu, Raindel Shachar, Swanson Steven, Sekar Vyas, and Seshan Srinivasan. 2018. Hyperloop: Group-based NIC-offloading to accelerate replicated transactions in multi-tenant storage systems. In Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication (SIGCOMM’18). ACM, New York, NY, 297312.Google ScholarGoogle ScholarDigital LibraryDigital Library
  49. [49] Kung H. T. and Robinson John T.. 1981. On optimistic methods for concurrency control. ACM Transactions on Database Systems 6, 2 (1981), 213226.Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. [50] Lamport Leslie, Malkhi Dahlia, and Zhou Lidong. 2009. Vertical Paxos and primary-backup replication. In Proceedings of the 28th Annual ACM Symposium on Principles of Distributed Computing (PODC’09). ACM, New York, NY, 312313.Google ScholarGoogle ScholarDigital LibraryDigital Library
  51. [51] Lee Changmin, Shin Wonjae, Kim Dae Jeong, Yu Yongjun, Kim Sung-Joon, Ko Taekyeong, Seo Deokho, et al. 2020. NVDIMM-C: A byte-addressable non-volatile memory module for compatibility with standard DDR memory interfaces. In Proceedings of the IEEE International Symposium on High Performance Computer Architecture (HPCA’20). IEEE, Los Alamitos, CA, 502514.Google ScholarGoogle ScholarCross RefCross Ref
  52. [52] Lee SeungSeob, Yu Yanpeng, Tang Yupeng, Khandelwal Anurag, Zhong Lin, and Bhattacharjee Abhishek. 2021. MIND: In-network memory management for disaggregated data centers. In Proceedings of the ACM SIGOPS 28th Symposium on Operating Systems Principles (SOSP’21). ACM, New York, NY, 488504.Google ScholarGoogle ScholarDigital LibraryDigital Library
  53. [53] Lee Se Kwon, Mohan Jayashree, Kashyap Sanidhya, Kim Taesoo, and Chidambaram Vijay. 2019. Recipe: Converting concurrent DRAM indexes to persistent-memory indexes. In Proceedings of the 27th ACM Symposium on Operating Systems Principles (SOSP’19). ACM, New York, NY, 462477.Google ScholarGoogle ScholarDigital LibraryDigital Library
  54. [54] Lim Kevin T., Chang Jichuan, Mudge Trevor N., Ranganathan Parthasarathy, Reinhardt Steven K., and Wenisch Thomas F.. 2009. Disaggregated memory for expansion and sharing in blade servers. In Proceedings of the 36th International Symposium on Computer Architecture (ISCA’09). ACM, New York, NY, 267278.Google ScholarGoogle ScholarDigital LibraryDigital Library
  55. [55] Lim Kevin T., Turner Yoshio, Santos Jose Renato, AuYoung Alvin, Chang Jichuan, Ranganathan Parthasarathy, and Wenisch Thomas F.. 2012. System-level implications of disaggregated memory. In Proceedings of the 18th IEEE International Symposium on High Performance Computer Architecture (HPCA’12). IEEE, Los Alamitos, CA, 189200.Google ScholarGoogle ScholarDigital LibraryDigital Library
  56. [56] Lin Qian, Chang Pengfei, Chen Gang, Ooi Beng Chin, Tan Kian-Lee, and Wang Zhengkui. 2016. Towards a non-2PC transaction management in distributed database systems. In Proceedings of the 2016 International Conference on Management of Data (SIGMOD’16). ACM, New York, NY, 16591674.Google ScholarGoogle ScholarDigital LibraryDigital Library
  57. [57] Lu Youyou, Shu Jiwu, Chen Youmin, and Li Tao. 2017. Octopus: An RDMA-enabled distributed persistent memory file system. In Proceedings of the 2017 USENIX Annual Technical Conference (USENIX ATC’17). 773785.Google ScholarGoogle Scholar
  58. [58] Ma Teng, Zhang Mingxing, Chen Kang, Song Zhuo, Wu Yongwei, and Qian Xuehai. 2020. AsymNVM: An efficient framework for implementing persistent data structures on asymmetric NVM architecture. In Proceedings of the Architectural Support for Programming Languages and Operating Systems (ASPLOS’20). ACM, New York, NY, 757773.Google ScholarGoogle ScholarDigital LibraryDigital Library
  59. [59] Mu Shuai, Cui Yang, Zhang Yang, Lloyd Wyatt, and Li Jinyang. 2014. Extracting more concurrency from distributed transactions. In Proceedings of the 11th USENIX Symposium on Operating Systems Design and Implementation (OSDI’14). 479494.Google ScholarGoogle Scholar
  60. [60] Novakovic Stanko, Shan Yizhou, Kolli Aasheesh, Cui Michael, Zhang Yiying, Eran Haggai, Pismenny Boris, et al. 2019. Storm: A fast transactional dataplane for remote data structures. In Proceedings of the 12th ACM International Conference on Systems and Storage (SYSTOR’19). ACM, New York, NY, 97108.Google ScholarGoogle ScholarDigital LibraryDigital Library
  61. [61] Oracle. 2022. What Is OLTP? Retrieved February 2, 2023 from https://www.oracle.com/database/what-is-oltp/.Google ScholarGoogle Scholar
  62. [62] Research Vmware. 2021. Remote Memory. Retrieved February 2, 2023 from https://research.vmware.com/projects/remote-memory.Google ScholarGoogle Scholar
  63. [63] Ruan Zhenyuan, Schwarzkopf Malte, Aguilera Marcos K., and Belay Adam. 2020. AIFM: High-performance, application-integrated far memory. In Proceedings of the 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI’20). 315332.Google ScholarGoogle Scholar
  64. [64] Schuh Henry N., Liang Weihao, Liu Ming, Nelson Jacob, and Krishnamurthy Arvind. 2021. Xenic: SmartNIC-accelerated distributed transactions. In Proceedings of the ACM SIGOPS 28th Symposium on Operating Systems Principles (SOSP’21). ACM, New York, NY, 740755.Google ScholarGoogle ScholarDigital LibraryDigital Library
  65. [65] Shamis Alex, Renzelmann Matthew, Novakovic Stanko, Chatzopoulos Georgios, Dragojevic Aleksandar, Narayanan Dushyanth, and Castro Miguel. 2019. Fast general distributed transactions with opacity. In Proceedings of the 2019 International Conference on Management of Data (SIGMOD’19). ACM, New York, NY, 433448.Google ScholarGoogle ScholarDigital LibraryDigital Library
  66. [66] Shan Yizhou, Huang Yutong, Chen Yilun, and Zhang Yiying. 2018. LegoOS: A disseminated, distributed OS for hardware resource disaggregation. In Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI’18). 6987.Google ScholarGoogle Scholar
  67. [67] Shan Yizhou, Tsai Shin-Yeh, and Zhang Yiying. 2017. Distributed shared persistent memory. In Proceedings of the 2017 Symposium on Cloud Computing (SoCC’17). ACM, New York, NY, 323337.Google ScholarGoogle ScholarDigital LibraryDigital Library
  68. [68] Shrivastav Vishal, Valadarsky Asaf, Ballani Hitesh, Costa Paolo, Lee Ki-Suh, Wang Han, Agarwal Rachit, and Weatherspoon Hakim. 2019. Shoal: A network architecture for disaggregated racks. In Proceedings of the 16th USENIX Symposium on Networked Systems Design and Implementation (NSDI’19). 255270.Google ScholarGoogle Scholar
  69. [69] Talpey Tom, Hurson Tony, Agarwal Gaurav, and Reu Tom. 2020. RDMA Extensions for Enhanced Memory Placement. Retrieved February 2, 2023 from https://tools.ietf.org/html/draft-talpey-rdma-commit-01.Google ScholarGoogle Scholar
  70. [70] TATP. 2011. Telecom Application Transaction Processing Benchmark. Retrieved February 2, 2023 from http://tatpbenchmark.sourceforge.net/.Google ScholarGoogle Scholar
  71. [71] Team The H-Store. 2022. SmallBank Benchmark. Retrieved February 2, 2023 from https://hstore.cs.brown.edu/documentation/deployment/benchmarks/smallbank/.Google ScholarGoogle Scholar
  72. [72] NVIDIA Corporation. 2023. RDMA Aware Networks Programming User Manual v1.7. Retrieved February 2, 2023 from https://docs.nvidia.com/networking/display/RDMAAwareProgrammingv17/RDMA+Aware+Networks+Programming+User+Manual.Google ScholarGoogle Scholar
  73. [73] Thoziyoor Shyamkumar, Ahn Jung Ho, Monchiero Matteo, Brockman Jay B., and Jouppi Norman P.. 2008. A comprehensive memory modeling tool and its application to the design and analysis of future memory hierarchies. In Proceedings of the 35th International Symposium on Computer Architecture (ISCA’08). IEEE, Los Alamitos, CA, 5162.Google ScholarGoogle ScholarDigital LibraryDigital Library
  74. [74] Tirmazi Muhammad, Barker Adam, Deng Nan, Haque Md. E., Qin Zhijing Gene, Hand Steven, Harchol-Balter Mor, and Wilkes John. 2020. Borg: The next generation. In Proceedings of the 15th EuroSys Conference (EuroSys’20). ACM, New York, NY, Article 30, 14 pages.Google ScholarGoogle ScholarDigital LibraryDigital Library
  75. [75] Tsai Shin-Yeh, Shan Yizhou, and Zhang Yiying. 2020. Disaggregating persistent memory and controlling them remotely: An exploration of passive disaggregated key-value stores. In Proceedings of the 2020 USENIX Annual Technical Conference (USENIX ATC’20). 3348.Google ScholarGoogle Scholar
  76. [76] Tsai Shin-Yeh and Zhang Yiying. 2017. LITE kernel RDMA support for datacenter applications. In Proceedings of the 26th Symposium on Operating Systems Principles (SOSP’17). ACM, New York, NY, 306324.Google ScholarGoogle ScholarDigital LibraryDigital Library
  77. [77] Verbitski Alexandre, Gupta Anurag, Saha Debanjan, Brahmadesam Murali, Gupta Kamal, Mittal Raman, Krishnamurthy Sailesh, Maurice Sandor, Kharatishvili Tengiz, and Bao Xiaofeng. 2017. Amazon Aurora: Design considerations for high throughput cloud-native relational databases. In Proceedings of the 2017 ACM International Conference on Management of Data (SIGMOD’17). ACM, New York, NY, 10411052.Google ScholarGoogle ScholarDigital LibraryDigital Library
  78. [78] Wang Chenxi, Ma Haoran, Liu Shi, Li Yuanqi, Ruan Zhenyuan, Nguyen Khanh, Bond Michael D., Netravali Ravi, Kim Miryung, and Xu Guoqing Harry. 2020. Semeru: A memory-disaggregated managed runtime. In Proceedings of the 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI’20). 261280.Google ScholarGoogle Scholar
  79. [79] Wang Jia-Chen, Ding Ding, Wang Huan, Christensen Conrad, Wang Zhaoguo, Chen Haibo, and Li Jinyang. 2021. Polyjuice: High-performance transactions via learned concurrency control. In Proceedings of the 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI’21). 198216.Google ScholarGoogle Scholar
  80. [80] Webcast Live. 2018. Extending RDMA for persistent memory over fabrics. In Proceedings of the SNIA Networking Storage Forum.Google ScholarGoogle Scholar
  81. [81] Wei Xingda, Dong Zhiyuan, Chen Rong, and Chen Haibo. 2018. Deconstructing RDMA-enabled distributed transactions: Hybrid is better! In Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI’18). 233251.Google ScholarGoogle Scholar
  82. [82] Wei Xingda, Shi Jiaxin, Chen Yanzhe, Chen Rong, and Chen Haibo. 2015. Fast in-memory transaction processing using RDMA and HTM. In Proceedings of the 25th Symposium on Operating Systems Principles (SOSP’15). ACM, New York, NY, 87104.Google ScholarGoogle ScholarDigital LibraryDigital Library
  83. [83] Wei Xingda, Xie Xiating, Chen Rong, Chen Haibo, and Zang Binyu. 2021. Characterizing and optimizing remote persistent memory with RDMA and NVM. In Proceedings of the 2021 USENIX Annual Technical Conference (USENIX ATC’21). 523536.Google ScholarGoogle Scholar
  84. [84] Wong H.-S. Philip, Raoux Simone, Kim SangBum, Liang Jiale, Reifenberg John P., Rajendran Bipin, Asheghi Mehdi, and Goodson Kenneth E.. 2010. Phase change memory. Proceedings of the IEEE 98, 12 (2010), 22012227.Google ScholarGoogle ScholarCross RefCross Ref
  85. [85] Xie Chao, Su Chunzhi, Kapritsos Manos, Wang Yang, Yaghmazadeh Navid, Alvisi Lorenzo, and Mahajan Prince. 2014. Salt: Combining ACID and BASE in a distributed database. In Proceedings of the 11th USENIX Symposium on Operating Systems Design and Implementation (OSDI’14). 495509.Google ScholarGoogle Scholar
  86. [86] Xie Chao, Su Chunzhi, Littley Cody, Alvisi Lorenzo, Kapritsos Manos, and Wang Yang. 2015. High-performance ACID via modular concurrency control. In Proceedings of the 25th Symposium on Operating Systems Principles (SOSP’15). ACM, New York, NY, 279294.Google ScholarGoogle ScholarDigital LibraryDigital Library
  87. [87] Yang Jian, Izraelevitz Joseph, and Swanson Steven. 2019. Orion: A distributed file system for non-volatile main memory and RDMA-capable networks. In Proceedings of the 17th USENIX Conference on File and Storage Technologies (FAST’19). 221234.Google ScholarGoogle Scholar
  88. [88] Yang Jian, Izraelevitz Joseph, and Swanson Steven. 2020. FileMR: Rethinking RDMA networking for scalable persistent memory. In Proceedings of the 17th USENIX Symposium on Networked Systems Design and Implementation (NSDI’20). 111125.Google ScholarGoogle Scholar
  89. [89] Yang Jian, Kim Juno, Hoseinzadeh Morteza, Izraelevitz Joseph, and Swanson Steven. 2020. An empirical guide to the behavior and use of scalable persistent memory. In Proceedings of the 18th USENIX Conference on File and Storage Technologies (FAST’20). 169182.Google ScholarGoogle ScholarDigital LibraryDigital Library
  90. [90] Yang Juncheng, Yue Yao, and Rashmi K. V.. 2020. A large scale analysis of hundreds of in-memory cache clusters at Twitter. In Proceedings of the 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI’20). 191208.Google ScholarGoogle Scholar
  91. [91] Zamanian Erfan, Binnig Carsten, Harris Tim, and Kraska Tim. 2017. The end of a myth: Distributed transactions can scale. Proceedings of the VLDB Endowment 10, 6 (Feb.2017), 685696.Google ScholarGoogle ScholarDigital LibraryDigital Library
  92. [92] Zamanian Erfan, Shun Julian, Binnig Carsten, and Kraska Tim. 2020. Chiller: Contention-centric transaction execution and data partitioning for modern networks. In Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data (SIGMOD’20). ACM, New York, NY, 511526.Google ScholarGoogle ScholarDigital LibraryDigital Library
  93. [93] Zhang Irene, Sharma Naveen Kr., Szekeres Adriana, Krishnamurthy Arvind, and Ports Dan R. K.. 2015. Building consistent transactions with inconsistent replication. In Proceedings of the 25th Symposium on Operating Systems Principles (SOSP’15). ACM, New York, NY, 263278.Google ScholarGoogle ScholarDigital LibraryDigital Library
  94. [94] Zhang Ming, Hua Yu, Zuo Pengfei, and Liu Lurong. 2022. FORD: Fast one-sided RDMA-based distributed transactions for disaggregated persistent memory. In Proceedings of the 20th USENIX Conference on File and Storage Technologies (FAST’22). 5168.Google ScholarGoogle Scholar
  95. [95] Zhang Yiying, Yang Jian, Memaripour Amirsaman, and Swanson Steven. 2015. Mojim: A reliable and highly-available non-volatile memory system. In Proceedings of the 20th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS’15). ACM, New York, NY, 318.Google ScholarGoogle ScholarDigital LibraryDigital Library
  96. [96] Zuo Pengfei, Sun Jiazhao, Yang Liu, Zhang Shuangwu, and Hua Yu. 2021. One-sided RDMA-conscious extendible hashing for disaggregated memory. In Proceedings of the 2021 USENIX Annual Technical Conference (USENIX ATC’21). 1529.Google ScholarGoogle Scholar

Index Terms

  1. Localized Validation Accelerates Distributed Transactions on Disaggregated Persistent Memory

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in

        Full Access

        • Published in

          cover image ACM Transactions on Storage
          ACM Transactions on Storage  Volume 19, Issue 3
          August 2023
          233 pages
          ISSN:1553-3077
          EISSN:1553-3093
          DOI:10.1145/3604654
          Issue’s Table of Contents

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 19 June 2023
          • Online AM: 21 January 2023
          • Accepted: 6 January 2023
          • Revised: 29 October 2022
          • Received: 13 June 2022
          Published in tos Volume 19, Issue 3

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader

        Full Text

        View this article in Full Text.

        View Full Text