{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T06:27:00Z","timestamp":1778048820335,"version":"3.51.4"},"reference-count":69,"publisher":"Association for Computing Machinery (ACM)","issue":"3","funder":[{"name":"the National Key Research and Development Program of China","award":["No.2023YFB4502701"],"award-info":[{"award-number":["No.2023YFB4502701"]}]},{"name":"the Key Research and Development Program of Guangdong Province","award":["No. 2021B0101400003"],"award-info":[{"award-number":["No. 2021B0101400003"]}]},{"DOI":"10.13039\/501100002858","name":"the China Postdoctoral Science Foundation","doi-asserted-by":"crossref","award":["No.2024M751011"],"award-info":[{"award-number":["No.2024M751011"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"crossref"}]},{"name":"the Postdoctor Project of Hubei Province","award":["No.2004HBBHCXA027"],"award-info":[{"award-number":["No.2004HBBHCXA027"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. ACM Manag. Data"],"published-print":{"date-parts":[[2025,6,17]]},"abstract":"<jats:p>Rapid increase of storage and network bandwidth incurs higher CPU consumption in modern data systems. This phenomenon is particularly evident for log-structured merged key-value stores (LSM-KVS), which rely on resource-intensive background operations to flush and compact disk data. While extensive research has been conducted to reduce the CPU overhead of background compaction, less attention has been paid to background flushing, which can also consume a significant amount of valuable CPU cycles and disrupt CPU caches, ultimately impacting overall performance.<\/jats:p>\n                  <jats:p>In this paper, we propose DFlush, a novel solution that uses DPUs to offload background flush operations to reduce its CPU cost. DPUs are an appealing choice for this goal due to their cost-effectiveness, ease of programming, and widespread deployment. However, their complex hardware architecture requires careful design of both the data and control planes. To fully harness the DPU's capabilities, DFlush decomposes a flush job into fine-grained steps, mapped them to DPU hardware units, and accelerates them through pipeline, data, and channel parallelism, ensuring data-plane efficiency. It also introduces an adaptive control plane that dynamically schedules flush jobs from different LSM-KVS instances based on their priority, reducing write stall and tail latency. Our experiments on a real DPU platform with an industrial-grade LSM-KVS show that DFlush delivers higher throughput, significantly lower tail latency, and saves up to dozens of CPU cores per LSM-KVS server while reducing energy consumption.<\/jats:p>","DOI":"10.1145\/3725284","type":"journal-article","created":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T21:23:29Z","timestamp":1750281809000},"page":"1-28","source":"Crossref","is-referenced-by-count":2,"title":["DFlush: DPU-Offloaded Flush for Disaggregated LSM-based Key-Value Stores"],"prefix":"10.1145","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0157-6496","authenticated-orcid":false,"given":"Chen","family":"Ding","sequence":"first","affiliation":[{"name":"Huazhong University of Science and Technology, WNLO, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7757-4083","authenticated-orcid":false,"given":"Kai","family":"Lu","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology, WNLO, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-7405-3302","authenticated-orcid":false,"given":"Quanyi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology, WNLO, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-0578-0397","authenticated-orcid":false,"given":"Zekun","family":"Ye","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology, WNLO, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9358-9373","authenticated-orcid":false,"given":"Ting","family":"Yao","sequence":"additional","affiliation":[{"name":"Huawei Cloud Computing Technology Co., Ltd., Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-8169-294X","authenticated-orcid":false,"given":"Daohui","family":"Wang","sequence":"additional","affiliation":[{"name":"Huawei Cloud Computing Technology Co., Ltd., Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7971-5014","authenticated-orcid":false,"given":"Huatao","family":"Wu","sequence":"additional","affiliation":[{"name":"Huawei Cloud Computing Technology Co., Ltd., Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4160-9475","authenticated-orcid":false,"given":"Jiguang","family":"Wan","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology, WNLO, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,6,18]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.14778\/2757807.2757810"},{"key":"e_1_2_1_2_1","unstructured":"AMD. 2023. Amd pensando infrastructure accelerators. https:\/\/www.intel.com\/content\/www\/us\/en\/products\/details\/network-io\/ipu.html"},{"key":"e_1_2_1_3_1","volume-title":"Proceedings of the 2019 USENIX Annual Technical Conference, USENIX ATC 2019","author":"Balmau Oana","year":"2019","unstructured":"Oana Balmau, Florin Dinu, Willy Zwaenepoel, Karan Gupta, Ravishankar Chandhiramoorthi, and Diego Didona. 2019. SILK: Preventing Latency Spikes in Log-Structured Merge Key-Value Stores. In Proceedings of the 2019 USENIX Annual Technical Conference, USENIX ATC 2019, Renton, WA, USA, July 10--12, 2019, Dahlia Malkhi and Dan Tsafrir (Eds.). USENIX Association, 753--766. https:\/\/www.usenix.org\/conference\/atc19\/presentation\/balmau"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3373376.3378504"},{"key":"e_1_2_1_5_1","unstructured":"Broadcom. 2020. Broadcom stingray smartnic accelerates baidu cloud services. https:\/\/www.broadcom.com\/company\/news\/product-releases\/53106"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/HCS52781.2021.9567066"},{"key":"e_1_2_1_7_1","volume-title":"Proceedings of the 2018 USENIX Annual Technical Conference, USENIX ATC 2018","author":"Chan Helen H. W.","year":"2018","unstructured":"Helen H. W. Chan, Yongkun Li, Patrick P. C. Lee, and Yinlong Xu. 2018. HashKV: Enabling Efficient Updates in KV Storage via Hashing. In Proceedings of the 2018 USENIX Annual Technical Conference, USENIX ATC 2018, Boston, MA, USA, July 11--13, 2018, Haryadi S. Gunawi and Benjamin C. Reed (Eds.). USENIX Association, 1007--1019. https:\/\/www.usenix.org\/conference\/atc18\/presentation\/chan"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1365815.1365816"},{"key":"e_1_2_1_9_1","unstructured":"Alibaba Cloud. 2022. A detailed explanation about alibaba cloud cipu. https:\/\/www.alibabacloud.com\/blog\/599183"},{"key":"e_1_2_1_10_1","unstructured":"Databricks. 2024. RocksDB State Store for Databricks. https:\/\/docs.databricks.com\/en\/structured-streaming\/rocksdb-state-store.html"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3035918.3064054"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3183713.3196927"},{"key":"e_1_2_1_13_1","volume-title":"D2Comp: Efficient Offload of LSM-tree Compaction with Data Processing Units on Disaggregated Storage. ACM Transactions on Architecture and Code Optimization","author":"Ding Chen","year":"2024","unstructured":"Chen Ding, Jian Zhou, Kai Lu, Sicen Li, Yiqin Xiong, Jiguang Wan, and Ling Zhan. 2024. D2Comp: Efficient Offload of LSM-tree Compaction with Data Processing Units on Disaggregated Storage. ACM Transactions on Architecture and Code Optimization (2024)."},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3605573.3605633"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3483840"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3589772"},{"key":"e_1_2_1_17_1","unstructured":"Facebook. 2024. RocksDB A persistent key-value store for fast storage enviroments. http:\/\/rocksdb.org\/"},{"key":"e_1_2_1_18_1","volume-title":"Azure Accelerated Networking: SmartNICs in the Public Cloud. In 15th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2018","author":"Firestone Daniel","year":"2018","unstructured":"Daniel Firestone, Andrew Putnam, Sambrama Mundkur, Derek Chiou, Alireza Dabagh, Mike Andrewartha, Hari Angepat, Vivek Bhanu, Adrian M. Caulfield, Eric S. Chung, Harish Kumar Chandrappa, Somesh Chaturmohta, Matt Humphrey, Jack Lavier, Norman Lam, Fengfen Liu, Kalin Ovtcharov, Jitu Padhye, Gautham Popuri, Shachar Raindel, Tejas Sapre, Mark Shaw, Gabriel Silva, Madhan Sivakumar, Nisheeth Srivastava, Anshuman Verma, Qasim Zuhair, Deepak Bansal, Doug Burger, Kushagra Vaid, David A. Maltz, and Albert G. Greenberg. 2018. Azure Accelerated Networking: SmartNICs in the Public Cloud. In 15th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2018, Renton, WA, USA, April 9--11, 2018, Sujata Banerjee and Srinivasan Seshan (Eds.). USENIX Association, 51--66. https:\/\/www.usenix.org\/conference\/nsdi18\/presentation\/firestone"},{"key":"e_1_2_1_19_1","unstructured":"Google. 2024. LevelDB A fast key-value storage library. https:\/\/github.com\/google\/leveldb"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3579370.3594769"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3603269.3604880"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.14778\/3415478.3415535"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3448016.3457297"},{"key":"e_1_2_1_24_1","volume-title":"Proceedings of the 2020 USENIX Annual Technical Conference, USENIX ATC 2020, July 15--17","author":"Im Junsu","year":"2020","unstructured":"Junsu Im, Jinwook Bae, Chanwoo Chung, Arvind, and Sungjin Lee. 2020. PinK: High-speed In-storage Key-value Store with Bounded Tails. In Proceedings of the 2020 USENIX Annual Technical Conference, USENIX ATC 2020, July 15--17, 2020, Ada Gavrilovska and Erez Zadok (Eds.). USENIX Association, 173--187. https:\/\/www.usenix.org\/conference\/atc20\/presentation\/im"},{"key":"e_1_2_1_25_1","unstructured":"Intel. 2024. Infrastructure Processing Unit. https:\/\/www.intel.com\/content\/www\/us\/en\/products\/details\/network-io\/ipu.html"},{"key":"e_1_2_1_26_1","unstructured":"Peter Judge. 2022. Intel and google cloud jointly launch data center accelerator chip. https:\/\/www.datacenterdynamics.com\/en\/news\/intel-and-google-cloud-jointly-launch-data-center-accelerator-chip\/"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477132.3483565"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/1773912.1773922"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3341301.3359628"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3481913"},{"key":"e_1_2_1_31_1","volume-title":"Fisc: A Large-scale Cloud-native-oriented File System. In 21st USENIX Conference on File and Storage Technologies, FAST 2023","author":"Li Qiang","year":"2023","unstructured":"Qiang Li, Lulu Chen, Xiaoliang Wang, Shuo Huang, Qiao Xiang, Yuanyuan Dong, Wenhui Yao, Minfei Huang, Puyuan Yang, Shanyang Liu, Zhaosheng Zhu, Huayong Wang, Haonan Qiu, Derui Liu, Shaozong Liu, Yujie Zhou, Yaohui Wu, Zhiwu Wu, Shang Gao, Chao Han, Zicheng Luo, Yuchao Shao, Gexiao Tian, Zhongjie Wu, Zheng Cao, Jinbo Wu, Jiwu Shu, Jie Wu, and Jiesheng Wu. 2023. Fisc: A Large-scale Cloud-native-oriented File System. 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, 231--246. https:\/\/www.usenix.org\/conference\/fast23\/presentation\/li-qiang-fisc"},{"key":"e_1_2_1_32_1","volume-title":"Proceedings of the 2021 USENIX Annual Technical Conference, USENIX ATC 2021, July 14--16","author":"Li Yongkun","year":"2021","unstructured":"Yongkun Li, Zhen Liu, Patrick P. C. Lee, Jiayu Wu, Yinlong Xu, Yi Wu, Liu Tang, Qi Liu, and Qiu Cui. 2021b. Differentiated Key-Value Storage Management for Balanced I\/O Performance. In Proceedings of the 2021 USENIX Annual Technical Conference, USENIX ATC 2021, July 14--16, 2021, Irina Calciu and Geoff Kuenning (Eds.). USENIX Association, 673--687. https:\/\/www.usenix.org\/conference\/atc21\/presentation\/li-yongkun"},{"key":"e_1_2_1_33_1","volume-title":"The Nitro Project--Next Generation AWS Infrastructure. In Hot Chips: A Symposium on High Performance Chips.","author":"Liguori Anthony","year":"2018","unstructured":"Anthony Liguori. 2018. The Nitro Project--Next Generation AWS Infrastructure. In Hot Chips: A Symposium on High Performance Chips."},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3578338.3593577"},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3341302.3342079"},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/2749469.2749475"},{"key":"e_1_2_1_37_1","volume-title":"14th USENIX Conference on File and Storage Technologies, FAST 2016","author":"Lu Lanyue","year":"2016","unstructured":"Lanyue Lu, Thanumalayan Sankaranarayana Pillai, Andrea C. Arpaci-Dusseau, and Remzi H. Arpaci-Dusseau. 2016. WiscKey: Separating Keys from Values in SSD-conscious Storage. In 14th USENIX Conference on File and Storage Technologies, FAST 2016, Santa Clara, CA, USA, February 22--25, 2016, Angela Demke Brown and Florentina I. Popovici (Eds.). USENIX Association, 133--148. https:\/\/www.usenix.org\/conference\/fast16\/technical-sessions\/presentation\/lu"},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3492321.3519567"},{"key":"e_1_2_1_39_1","unstructured":"Marvell. 2023. Marvell octeon data processing units (dpus). https:\/\/www.marvell.com\/products\/data-processing-units.html"},{"key":"e_1_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.14778\/3415478.3415546"},{"key":"e_1_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3452296.3472940"},{"key":"e_1_2_1_42_1","unstructured":"NVIDIA. 2022. DPU POWER EFFICIENCY. https:\/\/dcmag.fr\/wp-content\/uploads\/2022\/11\/nvidia-dpu-power-efficiency-white-paper-2508650.pdf"},{"key":"e_1_2_1_43_1","unstructured":"NVIDIA. 2024a. BlueField-3 DPU. https:\/\/www.nvidia.com\/en-us\/networking\/products\/data-processing-unit\/"},{"key":"e_1_2_1_44_1","unstructured":"NVIDIA. 2024b. NVIDIA DOCA Software Framework. https:\/\/developer.nvidia.com\/networking\/doca"},{"key":"e_1_2_1_45_1","volume-title":"Rockset: Search and analytics database. https:\/\/rockset.com\/","author":"AI.","year":"2024","unstructured":"OpenAI. 2024. Rockset: Search and analytics database. https:\/\/rockset.com\/"},{"key":"e_1_2_1_46_1","volume-title":"19th USENIX Conference on File and Storage Technologies, FAST 2021","author":"Pan Satadru","year":"2021","unstructured":"Satadru Pan, Theano Stavrinos, Yunqiao Zhang, Atul Sikaria, Pavel Zakharov, Abhinav Sharma, Shiva Shankar P., Mike Shuey, Richard Wareing, Monika Gangapuram, Guanglei Cao, Christian Preseau, Pratap Singh, Kestutis Patiejunas, J. R. Tipton, Ethan Katz-Bassett, and Wyatt Lloyd. 2021. Facebook's Tectonic Filesystem: Efficiency from Exascale. In 19th USENIX Conference on File and Storage Technologies, FAST 2021, February 23--25, 2021, Marcos K. Aguilera and Gala Yadgar (Eds.). USENIX Association, 217--231. https:\/\/www.usenix.org\/conference\/fast21\/presentation\/pan"},{"key":"e_1_2_1_47_1","unstructured":"Hieu Pham. 2020. Remote Compactions in RocksDB-Cloud. https:\/\/rockset.com\/blog\/remote-compactions-in-rocksdb-cloud\/"},{"key":"e_1_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3329785.3329927"},{"key":"e_1_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477132.3483583"},{"key":"e_1_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132747.3132765"},{"key":"e_1_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477132.3483555"},{"key":"e_1_2_1_52_1","volume-title":"Disaggregating and Consolidating Network Functionalities with SuperNIC. CoRR","author":"Shan Yizhou","year":"2021","unstructured":"Yizhou Shan, Will Lin, Ryan Kosta, Arvind Krishnamurthy, and Yiying Zhang. 2021. Disaggregating and Consolidating Network Functionalities with SuperNIC. CoRR, Vol. abs\/2109.07744 (2021). showeprint[arXiv]2109.07744 https:\/\/arxiv.org\/abs\/2109.07744"},{"key":"e_1_2_1_53_1","volume-title":"Burstable Cloud Block Storage with Data Processing Units. In 18th USENIX Symposium on Operating Systems Design and Implementation, OSDI 2024","author":"Shu Junyi","year":"2024","unstructured":"Junyi Shu, Kun Qian, Ennan Zhai, Xuanzhe Liu, and Xin Jin. 2024. Burstable Cloud Block Storage with Data Processing Units. In 18th USENIX Symposium on Operating Systems Design and Implementation, OSDI 2024, Santa Clara, CA, USA, July 10--12, 2024, Ada Gavrilovska and Douglas B. Terry (Eds.). USENIX Association, 783--799. https:\/\/www.usenix.org\/conference\/osdi24\/presentation\/shu"},{"key":"e_1_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSST.2010.5496972"},{"key":"e_1_2_1_55_1","volume-title":"An Asynchronous Compaction Acceleration Scheme for Near-Data Processing-enabled LSM-Tree-based KV Stores. ACM Transactions on Embedded Computing Systems","author":"Sun Hui","year":"2023","unstructured":"Hui Sun, Bendong Lou, Chao Zhao, Deyan Kong, Chaowei Zhang, Jianzhong Huang, Yinliang Yue, and Xiao Qin. 2023. An Asynchronous Compaction Acceleration Scheme for Near-Data Processing-enabled LSM-Tree-based KV Stores. ACM Transactions on Embedded Computing Systems (2023)."},{"key":"e_1_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1145\/3633782"},{"key":"e_1_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE48307.2020.00113"},{"key":"e_1_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE60146.2024.00298"},{"key":"e_1_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE55515.2023.00217"},{"key":"e_1_2_1_60_1","volume-title":"LUDA: Boost LSM Key Value Store Compactions with GPUs. CoRR","author":"Xu Peng","year":"2020","unstructured":"Peng Xu, Jiguang Wan, Ping Huang, Xiaogang Yang, Chenlei Tang, Fei Wu, and Changsheng Xie. 2020. LUDA: Boost LSM Key Value Store Compactions with GPUs. CoRR, Vol. abs\/2004.03054 (2020). showeprint[arXiv]2004.03054 https:\/\/arxiv.org\/abs\/2004.03054"},{"key":"e_1_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.14778\/3554821.3554830"},{"key":"e_1_2_1_62_1","volume-title":"Proc. 33rd Int. Conf. Massive Storage Syst. Technol.(MSST). 1--13","author":"Yao Ting","year":"2017","unstructured":"Ting Yao, Jiguang Wan, Ping Huang, Xubin He, Qingxin Gui, Fei Wu, and Changsheng Xie. 2017. A light-weight compaction tree to reduce I\/O amplification toward efficient key-value stores. In Proc. 33rd Int. Conf. Massive Storage Syst. Technol.(MSST). 1--13."},{"key":"e_1_2_1_63_1","volume-title":"ADOC: Automatically Harmonizing Dataflow Between Components in Log-Structured Key-Value Stores for Improved Performance. In 21st USENIX Conference on File and Storage Technologies, FAST 2023","author":"Yu Jinghuan","year":"2023","unstructured":"Jinghuan Yu, Sam H. Noh, Young-ri Choi, and Chun Jason Xue. 2023. ADOC: Automatically Harmonizing Dataflow Between Components in Log-Structured Key-Value Stores for Improved Performance. 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, 65--80. https:\/\/www.usenix.org\/conference\/fast23\/presentation\/yu"},{"key":"e_1_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1145\/3654927"},{"key":"e_1_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1145\/3579371.3589077"},{"key":"e_1_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.14778\/3681954.3682002"},{"key":"e_1_2_1_67_1","volume-title":"FPGA-Accelerated Compactions for LSM-based Key-Value Store. In 18th USENIX Conference on File and Storage Technologies, FAST 2020","author":"Zhang Teng","year":"2020","unstructured":"Teng Zhang, Jianying Wang, Xuntao Cheng, Hao Xu, Nanlong Yu, Gui Huang, Tieying Zhang, Dengcheng He, Feifei Li, Wei Cao, Zhongdong Huang, and Jianling Sun. 2020. FPGA-Accelerated Compactions for LSM-based Key-Value Store. 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, 225--237. https:\/\/www.usenix.org\/conference\/fast20\/presentation\/zhang-teng"},{"key":"e_1_2_1_68_1","volume-title":"22nd USENIX Conference on File and Storage Technologies, FAST 2024","author":"Zhang Weidong","year":"2024","unstructured":"Weidong Zhang, Erci Xu, Qiuping Wang, Xiaolu Zhang, Yuesheng Gu, Zhenwei Lu, Tao Ouyang, Guanqun Dai, Wenwen Peng, Zhe Xu, Shuo Zhang, Dong Wu, Yilei Peng, Tianyun Wang, Haoran Zhang, Jiasheng Wang, Wenyuan Yan, Yuanyuan Dong, Wenhui Yao, Zhongjie Wu, Lingjun Zhu, Chao Shi, Yinhu Wang, Rong Liu, Junping Wu, Jiaji Zhu, and Jiesheng Wu. 2024b. What's the Story in EBS Glory: Evolutions and Lessons in Building Cloud Block Store. In 22nd USENIX Conference on File and Storage Technologies, FAST 2024, Santa Clara, CA, USA, February 27--29, 2024, Xiaosong Ma and Youjip Won (Eds.). USENIX Association, 277--291. https:\/\/www.usenix.org\/conference\/fast24\/presentation\/zhang-weidong"},{"key":"e_1_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.1145\/3673038.3673123"}],"container-title":["Proceedings of the ACM on Management of Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3725284","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T18:53:20Z","timestamp":1774983200000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3725284"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,17]]},"references-count":69,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,6,17]]}},"alternative-id":["10.1145\/3725284"],"URL":"https:\/\/doi.org\/10.1145\/3725284","relation":{},"ISSN":["2836-6573"],"issn-type":[{"value":"2836-6573","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,17]]}}}