Xinhao Min
Skip Abstract Section
Abstract
Disaggregated memory separates compute and memory resources into independent pools connected by fast RDMA (Remote Direct Memory Access) networks, which can improve memory utilization, reduce cost, and enable elastic scaling of compute and memory resources. Hash indexes provide high-performance single-point operations and are widely used in distributed systems and databases. However, under disaggregated memory, existing hash indexes suffer from write performance degradation due to high resize overhead and concurrency control overhead. Traditional write-optimized hash indexes are not efficient for disaggregated memory and sacrifice read performance.
In this paper, we propose SepHash, a write-optimized hash index for disaggregated memory. First, SepHash proposes a two-level separate segment structure that significantly reduces the bandwidth consumption of resize operations. Second, SepHash employs a low-latency concurrency control strategy to eliminate unnecessary mutual exclusion and check overhead during insert operations. Finally, SepHash designs an efficient cache and filter to accelerate read operations. The evaluation results show that, compared to state-of-the-art distributed hash indexes, SepHash achieves a 3.3X higher write performance while maintaining comparable read performance.
- 2023. Memcached-a distributed memory object caching system. https://memcached.org/.Google Scholar
- Paulo Sérgio Almeida. 2023. A Case for Partitioned Bloom Filters. IEEE Trans. Computers 72, 6 (2023), 1681--1691. Google ScholarDigital Library
- Berk Atikoglu, Yuehai Xu, Eitan Frachtenberg, Song Jiang, and Mike Paleczny. 2012. Workload analysis of a large-scale key-value store. In ACM SIGMETRICS/PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS '12, London, United Kingdom, June 11--15, 2012, Peter G. Harrison, Martin F. Arlitt, and Giuliano Casale (Eds.). ACM, 53--64. Google ScholarDigital Library
- Alex D. Breslow and Nuwan Jayasena. 2020. Morton filters: fast, compressed sparse cuckoo filters. VLDB J. 29, 2--3 (2020), 731--754. Google ScholarCross Ref
- Wei Cao, Yingqiang Zhang, Xinjun Yang, Feifei Li, Sheng Wang, Qingda Hu, Xuntao Cheng, Zongzhi Chen, Zhenjun Liu, Jing Fang, Bo Wang, Yuhui Wang, Haiqing Sun, Ze Yang, Zhushi Cheng, Sen Chen, Jian Wu, Wei Hu, Jianwei Zhao, Yusong Gao, Songlu Cai, Yunyang Zhang, and Jiawang Tong. 2021. PolarDB Serverless: A Cloud Native Database for Disaggregated Data Centers. In SIGMOD '21: International Conference on Management of Data, Virtual Event, China, June 20--25, 2021, Guoliang Li, Zhanhuai Li, Stratos Idreos, and Divesh Srivastava (Eds.). ACM, 2477--2489. Google ScholarDigital Library
- Zhichao Cao, Siying Dong, Sagar Vemuri, and David H. C. Du. 2020. Characterizing, Modeling, and Benchmarking RocksDB Key-Value Workloads at Facebook. In 18th USENIX Conference on File and Storage Technologies, FAST 2020, Santa Clara, CA, USA, February 24--27, 2020, Sam H. Noh and Brent Welch (Eds.). USENIX Association, 209--223. https://www.usenix.org/conference/fast20/presentation/cao-zhichaoGoogle Scholar
- Xinyi Chen, Liangcheng Yu, Vincent Liu, and Qizhen Zhang. 2023. Cowbird: Freeing CPUs to Compute by Offloading the Disaggregation of Memory. In Proceedings of the ACM SIGCOMM 2023 Conference, ACM SIGCOMM 2023, New York, NY, USA, 10--14 September 2023, Henning Schulzrinne, Vishal Misra, Eddie Kohler, and David A. Maltz (Eds.). ACM, 1060--1073. Google ScholarDigital Library
- Youmin Chen, Youyou Lu, Fan Yang, Qing Wang, Yang Wang, and Jiwu Shu. 2020. FlatStore: An Efficient Log-Structured Key-Value Storage Engine for Persistent Memory. In ASPLOS '20: Architectural Support for Programming Languages and Operating Systems, Lausanne, Switzerland, March 16--20, 2020, James R. Larus, Luis Ceze, and Karin Strauss (Eds.). ACM, 1077--1091. Google ScholarDigital Library
- Zhangyu Chen, Yu Hua, Bo Ding, and Pengfei Zuo. 2020. Lock-free Concurrent Level Hashing for Persistent Memory. In 2020 USENIX Annual Technical Conference, USENIX ATC 2020, July 15--17, 2020, Ada Gavrilovska and Erez Zadok (Eds.). USENIX Association, 799--812. https://www.usenix.org/conference/atc20/presentation/chenGoogle Scholar
- Brian F. Cooper, Adam Silberstein, Erwin Tam, Raghu Ramakrishnan, and Russell Sears. 2010. Benchmarking cloud serving systems with YCSB. In Proceedings of the 1st ACM Symposium on Cloud Computing, SoCC 2010, Indianapolis, Indiana, USA, June 10--11, 2010, Joseph M. Hellerstein, Surajit Chaudhuri, and Mendel Rosenblum (Eds.). ACM, 143--154. Google ScholarDigital Library
- SM CXL Consortium et al. 2022. Compute express link: The breakthrough CPU-to-device interconnect. Retrieved February 2 (2022), 2023.Google Scholar
- Niv Dayan, Manos Athanassoulis, and Stratos Idreos. 2017. Monkey: Optimal Navigable Key-Value Store. In Proceedings of the 2017 ACM International Conference on Management of Data, SIGMOD Conference 2017, Chicago, IL, USA, May 14--19, 2017, Semih Salihoglu, Wenchao Zhou, Rada Chirkova, Jun Yang, and Dan Suciu (Eds.). ACM, 79--94. Google ScholarDigital Library
- Niv Dayan and Moshe Twitto. 2021. Chucky: A Succinct Cuckoo Filter for LSM-Tree. In SIGMOD '21: International Conference on Management of Data, Virtual Event, China, June 20--25, 2021, Guoliang Li, Zhanhuai Li, Stratos Idreos, and Divesh Srivastava (Eds.). ACM, 365--378. Google ScholarDigital Library
- Aleksandar Dragojevic, Dushyanth Narayanan, Miguel Castro, and Orion Hodson. 2014. FaRM: Fast Remote Memory. In Proceedings of the 11th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2014, Seattle, WA, USA, April 2--4, 2014, Ratul Mahajan and Ion Stoica (Eds.). USENIX Association, 401--414. https://www.usenix.org/conference/nsdi14/technical-sessions/dragojevi%C4%87Google Scholar
- Peter Xiang Gao, Akshay Narayan, Sagar Karandikar, João Carreira, Sangjin Han, Rachit Agarwal, Sylvia Ratnasamy, and Scott Shenker. 2016. Network Requirements for Resource Disaggregation. In 12th USENIX Symposium on Operating Systems Design and Implementation, OSDI 2016, Savannah, GA, USA, November 2--4, 2016, Kimberly Keeton and Timothy Roscoe (Eds.). USENIX Association, 249--264. https://www.usenix.org/conference/osdi16/technical-sessions/presentation/gaoGoogle Scholar
- Thomas E Hart, Paul E McKenney, Angela Demke Brown, and Jonathan Walpole. 2007. Performance of memory reclamation for lockless synchronization. J. Parallel and Distrib. Comput. 67, 12 (2007), 1270--1285.Google ScholarDigital Library
- IBM. 2018. Advancing Cloud with Memory Disaggregation. https://www.ibm.com/blogs/research/2018/01/advancing-cloud-memory-disaggregation/.Google Scholar
- Young Bae Jun, Sun Shin Ahn, and Hee Sik Kim. 2001. Quotient structures of some implicative algebras via fuzzy implicative filters. Fuzzy Sets Syst. 121, 2 (2001), 325--332. Google ScholarDigital Library
- Per-Åke Larson. 1988. Dynamic Hash Tables. Commun. ACM 31, 4 (1988), 446--457. Google ScholarDigital Library
- Se Kwon Lee, Soujanya Ponnapalli, Sharad Singhal, Marcos K. Aguilera, Kimberly Keeton, and Vijay Chidambaram. 2022. DINOMO: An Elastic, Scalable, High-Performance Key-Value Store for Disaggregated Persistent Memory. Proc. VLDB Endow. 15, 13 (2022), 4023--4037. Google ScholarDigital Library
- Huaicheng Li, Daniel S. Berger, Stanko Novakovic, Lisa Hsu, Daniel Ernst, Pantea Zardoshti, Monish Shah, Ishwar Agarwal, Mark D. Hill, Marcus Fontoura, and Ricardo Bianchini. 2022. First-generation Memory Disaggregation for Cloud Platforms. CoRR abs/2203.00241 (2022). 00241 arXiv:2203.00241 Google ScholarCross Ref
- Haifeng Li, Ke Liu, Ting Liang, Zuojun Li, Tianyue Lu, Hui Yuan, Yinben Xia, Yungang Bao, Mingyu Chen, and Yizhou Shan. 2023. HoPP: Hardware-Software Co-Designed Page Prefetching for Disaggregated Memory. In IEEE International Symposium on High-Performance Computer Architecture, HPCA 2023, Montreal, QC, Canada, February 25 - March 1, 2023. IEEE, 1168--1181. Google ScholarCross Ref
- Pengfei Li, Yu Hua, Pengfei Zuo, Zhangyu Chen, and Jiajie Sheng. 2023. ROLEX: A Scalable RDMA-oriented Learned Key-Value Store for Disaggregated Memory Systems. In 21st USENIX Conference on File and Storage Technologies, FAST 2023, Santa Clara, CA, USA, February 21--23, 2023, Ashvin Goel and Dalit Naor (Eds.). USENIX Association, 99--114. https://www.usenix.org/conference/fast23/presentation/li-pengfeiGoogle Scholar
- Hyeontaek Lim, Michael Kaminsky, and David G. Andersen. 2017. Cicada: Dependably Fast Multi-Core In-Memory Transactions. In Proceedings of the 2017 ACM International Conference on Management of Data, SIGMOD Conference 2017, Chicago, IL, USA, May 14--19, 2017, Semih Salihoglu, Wenchao Zhou, Rada Chirkova, Jun Yang, and Dan Suciu (Eds.). ACM, 21--35. Google ScholarDigital Library
- Baotong Lu, Xiangpeng Hao, Tianzheng Wang, and Eric Lo. 2020. Dash: Scalable Hashing on Persistent Memory. CoRR abs/2003.07302 (2020). arXiv:2003.07302 https://arxiv.org/abs/2003.07302Google Scholar
- Xuchuan Luo, Pengfei Zuo, Jiacheng Shen, Jiazhen Gu, Xin Wang, Michael R. Lyu, and Yangfan Zhou. 2023. SMART: A High-Performance Adaptive Radix Tree for Disaggregated Memory. In 17th USENIX Symposium on Operating Systems Design and Implementation, OSDI 2023, Boston, MA, USA, July 10--12, 2023, Roxana Geambasu and Ed Nightingale (Eds.). USENIX Association, 553--571. https://www.usenix.org/conference/osdi23/presentation/luoGoogle Scholar
- Wenhao Lv, Youyou Lu, Yiming Zhang, Peile Duan, and Jiwu Shu. 2022. InfiniFS: An Efficient Metadata Service for Large-Scale Distributed Filesystems. In 20th USENIX Conference on File and Storage Technologies, FAST 2022, Santa Clara, CA, USA, February 22--24, 2022, Dean Hildebrand and Donald E. Porter (Eds.). USENIX Association, 313--328. https://www.usenix.org/conference/fast22/presentation/lvGoogle Scholar
- Christopher Mitchell, Yifeng Geng, and Jinyang Li. 2013. Using One-Sided RDMA Reads to Build a Fast, CPU-Efficient Key-Value Store. In 2013 USENIX Annual Technical Conference, San Jose, CA, USA, June 26--28, 2013, Andrew Birrell and Emin Gun Sirer (Eds.). USENIX Association, 103--114. https://www.usenix.org/conference/atc13/technical-sessions/presentation/mitchellGoogle Scholar
- Sumit Kumar Monga, Sanidhya Kashyap, and Changwoo Min. 2021. Birds of a Feather Flock Together: Scaling RDMA RPCs with Flock. In SOSP '21: ACM SIGOPS 28th Symposium on Operating Systems Principles, Virtual Event / Koblenz, Germany, October 26--29, 2021, Robbert van Renesse and Nickolai Zeldovich (Eds.). ACM, 212--227. Google ScholarDigital Library
- Moohyeon Nam, Hokeun Cha, Young-ri Choi, Sam H. Noh, and Beomseok Nam. 2019. Write-Optimized Dynamic Hashing for Persistent Memory. In 17th USENIX Conference on File and Storage Technologies, FAST 2019, Boston, MA, February 25--28, 2019, Arif Merchant and Hakim Weatherspoon (Eds.). USENIX Association, 31--44. https://www.usenix.org/conference/fast19/presentation/namGoogle Scholar
- Rolf Neugebauer, Gianni Antichi, José Fernando Zazo, Yury Audzevich, Sergio López-Buedo, and Andrew W. Moore. 2018. Understanding PCIe performance for end host networking. In Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication, SIGCOMM 2018, Budapest, Hungary, August 20--25, 2018, Sergey Gorinsky and János Tapolcai (Eds.). ACM, 327--341. Google ScholarDigital Library
- Patrick O'Neil, Edward Cheng, Dieter Gawlick, and Elizabeth O'Neil. 1996. The log-structured merge-tree (LSM-tree). Acta Informatica 33 (1996), 351--385.Google ScholarDigital Library
- Prashant Pandey, Alex Conway, Joe Durie, Michael A. Bender, Martin Farach-Colton, and Rob Johnson. 2021. Vector Quotient Filters: Overcoming the Time/Space Trade-Off in Filter Design. In SIGMOD '21: International Conference on Management of Data, Virtual Event, China, June 20--25, 2021, Guoliang Li, Zhanhuai Li, Stratos Idreos, and Divesh Srivastava (Eds.). ACM, 1386--1399. Google ScholarDigital Library
- Waleed Reda, Marco Canini, Dejan Kostic, and Simon Peter. 2021. RDMA is Turing complete, we just did not know it yet! CoRR abs/2103.13351 (2021). arXiv:2103.13351 https://arxiv.org/abs/2103.13351Google Scholar
- Pedro Reviriego, Alfonso Sánchez-Macián, Stefan Walzer, Elena Merino Gómez, Shanshan Liu, and Fabrizio Lombardi. 2023. On the Privacy of Counting Bloom Filters. IEEE Trans. Dependable Secur. Comput. 20, 2 (2023), 1488--1499. Google ScholarDigital Library
- Yizhou Shan, Yutong Huang, Yilun Chen, and Yiying Zhang. 2018. LegoOS: A Disseminated, Distributed OS for Hardware Resource Disaggregation. In 13th USENIX Symposium on Operating Systems Design and Implementation, OSDI 2018, Carlsbad, CA, USA, October 8--10, 2018, Andrea C. Arpaci-Dusseau and Geoff Voelker (Eds.). USENIX Association, 69--87. https://www.usenix.org/conference/osdi18/presentation/shanGoogle Scholar
- Jiacheng Shen, Pengfei Zuo, Xuchuan Luo, Tianyi Yang, Yuxin Su, Yangfan Zhou, and Michael R. Lyu. 2023. FUSEE: A Fully Memory-Disaggregated Key-Value Store. In 21st USENIX Conference on File and Storage Technologies, FAST 2023, Santa Clara, CA, USA, February 21--23, 2023, Ashvin Goel and Dalit Naor (Eds.). USENIX Association, 81--98. https://www.usenix.org/conference/fast23/presentation/shenGoogle Scholar
- Vishal Shrivastav, Asaf Valadarsky, Hitesh Ballani, Paolo Costa, Ki Suh Lee, Han Wang, Rachit Agarwal, and Hakim Weatherspoon. 2019. Shoal: A Network Architecture for Disaggregated Racks. In 16th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2019, Boston, MA, February 26--28, 2019, Jay R. Lorch and Minlan Yu (Eds.). USENIX Association, 255--270. https://www.usenix.org/conference/nsdi19/presentation/shrivastavGoogle Scholar
- Håkan Sundell. 2005. Wait-free reference counting and memory management. In 19th IEEE International Parallel and Distributed Processing Symposium. IEEE, 10--pp.Google ScholarDigital Library
- Jéróme Vienne, Jitong Chen, Md. Wasi-ur-Rahman, Nusrat S. Islam, Hari Subramoni, and Dhabaleswar K. Panda. 2012. Performance Analysis and Evaluation of InfiniBand FDR and 40GigE RoCE on HPC and Cloud Computing Systems. In IEEE 20th Annual Symposium on High-Performance Interconnects, HOTI 2012, Santa Clara, CA, USA, August 22--24, 2012. IEEE Computer Society, 48--55. Google ScholarDigital Library
- Lukas Vogel, Alexander van Renen, Satoshi Imamura, Jana Giceva, Thomas Neumann, and Alfons Kemper. 2022. Plush: A Write-Optimized Persistent Log-Structured Hash-Table. Proc. VLDB Endow. 15, 11 (2022), 2895--2907. https://www.vldb.org/pvldb/vol15/p2895-vogel.pdfGoogle ScholarDigital Library
- Daniel G. Waddington, Clem Dickey, Luna Xu, Travis Janssen, Jantz Tran, and Kshitij A. Doshi. 2020. Evaluating Intel 3D-Xpoint NVDIMM Persistent Memory in the Context of a Key-Value Store. In IEEE International Symposium on Performance Analysis of Systems and Software, ISPASS 2020, Boston, MA, USA, August 23--25, 2020. IEEE, 202--211. Google ScholarCross Ref
- Qing Wang, Youyou Lu, and Jiwu Shu. 2022. Sherman: A Write-Optimized Distributed B+Tree Index on Disaggregated Memory. In SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12 - 17, 2022, Zachary G. Ives, Angela Bonifati, and Amr El Abbadi (Eds.). ACM, 1033--1048. Google ScholarDigital Library
- Ruihong Wang, Jianguo Wang, Prishita Kadam, M. Tamer Özsu, and Walid G. Aref. 2023. dLSM: An LSM-Based Index for Memory Disaggregation. In 39th IEEE International Conference on Data Engineering, ICDE 2023, Anaheim, CA, USA, April 3--7, 2023. IEEE, 2835--2849. Google ScholarCross Ref
- Tinggang Wang, Shuo Yang, Hideaki Kimura, Garret Swart, and Spyros Blanas. 2020, Efficient usage of one-sided rdma for linear probing. In Eleventh International Workshop on Accelerating Analytics and Data Management Systems Using Modern Processor and Storage Architectures (AMDS'20).Google Scholar
- Xingda Wei, Jiaxin Shi, Yanzhe Chen, Rong Chen, and Haibo Chen. 2015. Fast in-memory transaction processing using RDMA and HTM. In Proceedings of the 25th Symposium on Operating Systems Principles, SOSP 2015, Monterey, CA, USA, October 4--7, 2015, Ethan L. Miller and Steven Hand (Eds.). ACM, 87--104. Google ScholarDigital Library
- Xingda Wei, Xiating Xie, Rong Chen, Haibo Chen, and Binyu Zang. 2021. Characterizing and Optimizing Remote Persistent Memory with RDMA and NVM. In 2021 USENIX Annual Technical Conference, USENIX ATC 2021, July 14--16, 2021, Irina Calciu and Geoff Kuenning (Eds.). USENIX Association, 523--536. https://www.usenix.org/conference/atc21/presentation/weiGoogle Scholar
- Haosen Wen, Joseph Izraelevitz, Wentao Cai, H Alan Beadle, and Michael L Scott. 2018. Interval-based memory reclamation. ACM SIGPLAN Notices 53, 1 (2018), 1--13.Google ScholarDigital Library
- H.-S. Philip Wong, Simone Raoux, SangBum Kim, Jiale Liang, John P. Reifenberg, Bipin Rajendran, Mehdi Asheghi, and Kenneth E. Goodson. 2010. Phase Change Memory. Proc. IEEE 98, 12 (2010), 2201--2227. Google ScholarCross Ref
- Yahoo. 2015. YCSB-C. https://github.com/basicthinker/YCSB-C.Google Scholar
- Ting Yao, Jiguang Wan, Ping Huang, Yiwen Zhang, Zhiwen Liu, Changsheng Xie, and Xubin He. 2019. GearDB: A GC-free Key-Value Store on HM-SMR Drives with Gear Compaction. In 17th USENIX Conference on File and Storage Technologies, FAST 2019, Boston, MA, February 25--28, 2019, Arif Merchant and Hakim Weatherspoon (Eds.). USENIX Association, 159--171. https://www.usenix.org/conference/fast19/presentation/yaoGoogle Scholar
- Ting Yao, Yiwen Zhang, Jiguang Wan, Qiu Cui, Liu Tang, Hong Jiang, Changsheng Xie, and Xubin He. 2020. MatrixKV: Reducing Write Stalls and Write Amplification in LSM-tree Based KV Stores with Matrix Container in NVM. In 2020 USENIX Annual Technical Conference, USENIX ATC 2020, July 15--17, 2020, Ada Gavrilovska and Erez Zadok (Eds.). USENIX Association, 17--31. https://www.usenix.org/conference/atc20/presentation/yaoGoogle Scholar
- Wonsup Yoon, Jisu Ok, Jinyoung Oh, Sue Moon, and Youngjin Kwon. 2023. DiLOS: Do Not Trade Compatibility for Performance in Memory Disaggregation. In Proceedings of the Eighteenth European Conference on Computer Systems, EuroSys 2023, Rome, Italy, May 8--12, 2023, Giuseppe Antonio Di Luna, Leonardo Querzoni, Alexandra Fedorova, and Dushyanth Narayanan (Eds.). ACM, 266--282. Google ScholarDigital Library
- Erfan Zamanian, Carsten Binnig, Tim Kraska, and Tim Harris. 2016. The End of a Myth: Distributed Transactions Can Scale. CoRR abs/1607.00655 (2016). arXiv:1607.00655 http://arxiv.org/abs/1607.00655Google Scholar
- Huanchen Zhang, David G Andersen, Andrew Pavlo, Michael Kaminsky, Lin Ma, and Rui Shen. 2016. Reducing the storage overhead of main-memory OLTP databases with hybrid indexes. In Proceedings of the 2016 International Conference on Management of Data. 1567--1581.Google ScholarDigital Library
- Ming Zhang, Yu Hua, Pengfei Zuo, and Lurong Liu. 2022. FORD: Fast One-sided RDMA-based Distributed Transactions for Disaggregated Persistent Memory. In 20th USENIX Conference on File and Storage Technologies, FAST 2022, Santa Clara, CA, USA, February 22--24, 2022, Dean Hildebrand and Donald E. Porter (Eds.). USENIX Association, 51--68. https://www.usenix.org/conference/fast22/presentation/zhang-mingGoogle Scholar
- Qizhen Zhang, Xinyi Chen, Sidharth Sankhe, Zhilei Zheng, Ke Zhong, Sebastian Angel, Ang Chen, Vincent Liu, and Boon Thau Loo. 2022. Optimizing Data-intensive Systems in Disaggregated Data Centers with TELEPORT. In SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12 - 17, 2022, Zachary G. Ives, Angela Bonifati, and Amr El Abbadi (Eds.). ACM, 1345--1359. Google ScholarDigital Library
- Yingqiang Zhang, Chaoyi Ruan, Cheng Li, Jimmy Yang, Wei Cao, Feifei Li, Bo Wang, Jing Fang, Yuhui Wang, Jingze Huo, and Chao Bi. 2021. Towards Cost-Effective and Elastic Cloud Database Deployment via Memory Disaggregation. Proc. VLDB Endow. 14, 10 (2021), 1900--1912. Google ScholarDigital Library
- Yibo Zhu, Haggai Eran, Daniel Firestone, Chuanxiong Guo, Marina Lipshteyn, Yehonatan Liron, Jitendra Padhye, Shachar Raindel, Mohamad Haj Yahia, and Ming Zhang. 2015. Congestion Control for Large-Scale RDMA Deployments. In Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication, SIGCOMM 2015, London, United Kingdom, August 17--21, 2015, Steve Uhlig, Olaf Maennel, Brad Karp, and Jitendra Padhye (Eds.). ACM, 523--536. Google ScholarDigital Library
- Tobias Ziegler, Jacob Nelson-Slivon, Viktor Leis, and Carsten Binnig. 2023. Design Guidelines for Correct, Efficient, and Scalable Synchronization using One-Sided RDMA. Proc. ACM Manag. Data 1, 2 (2023), 131:1--131:26. Google ScholarDigital Library
- Tobias Ziegler, Sumukha Tumkur Vani, Carsten Binnig, Rodrigo Fonseca, and Tim Kraska. 2019. Designing Distributed Tree-based Index Structures for Fast RDMA-capable Networks. In Proceedings of the 2019 International Conference on Management of Data, SIGMOD Conference 2019, Amsterdam, The Netherlands, June 30 - July 5, 2019, Peter A. Boncz, Stefan Manegold, Anastasia Ailamaki, Amol Deshpande, and Tim Kraska (Eds.). ACM, 741--758. Google ScholarDigital Library
- Xiaomin Zou, Fang Wang, Dan Feng, Janxi Chen, Chaojie Liu, Fan Li, and Nan Su. 2020. HMEH: write-optimal extendible hashing for hybrid DRAM-NVM memory. Mass Storage Systems and Technologies (2020).Google Scholar
- Pengfei Zuo and Yu Hua. 2018. A Write-Friendly and Cache-Optimized Hashing Scheme for Non-Volatile Memory Systems. IEEE Trans. Parallel Distributed Syst. 29, 5 (2018), 985--998. Google ScholarCross Ref
- Pengfei Zuo, Yu Hua, and Jie Wu. 2018. Write-Optimized and High-Performance Hashing Index Scheme for Persistent Memory. In 13th USENIX Symposium on Operating Systems Design and Implementation, OSDI 2018, Carlsbad, CA, USA, October 8--10, 2018, Andrea C. Arpaci-Dusseau and Geoff Voelker (Eds.). USENIX Association, 461--476. https://www.usenix.org/conference/osdi18/presentation/zuoGoogle ScholarDigital Library
- Pengfei Zuo, Jiazhao Sun, Liu Yang, Shuangwu Zhang, and Yu Hua. 2021. One-sided RDMA-Conscious Extendible Hashing for Disaggregated Memory.. In USENIX Annual Technical Conference. 15--29.Google Scholar
Recommendations
Marlin: A Concurrent and Write-Optimized B+-tree Index on Disaggregated Memory
ICPP '23: Proceedings of the 52nd International Conference on Parallel ProcessingMemory disaggregation architecture can achieve higher resource utilization, independent scaling of CPUs and memory. Disaggregated memory systems manage memory resources and locate data by distributed index. However, existing distributed indexes suffer ...
Sherman: A Write-Optimized Distributed B+Tree Index on Disaggregated Memory
SIGMOD '22: Proceedings of the 2022 International Conference on Management of DataMemory disaggregation architecture physically separates CPU and memory into independent components, which are connected via high-speed RDMA networks, greatly improving resource utilization of databases. However, such an architecture poses unique ...
Write Activity Minimization for Nonvolatile Main Memory Via Scheduling and Recomputation
Nonvolatile memories such as Flash memory, phase change memory (PCM), and magnetic random access memory (MRAM) have many desirable characteristics for embedded systems to employ them as main memory. However, there are two common challenges we need to ...
Comments