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SNIA-SDC23-Zheng-KV-CSD-An-Ordered-Hardware-Accelerated.pdf

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1、1|2023 Triad National Security,LLC.All Rights Reserved.Virtual ConferenceSeptember 28-29,2021KV-CSDAn Ordered,HW-Accelerated KV Store For Rapid Data Insertion and QueriesQing Zheng,Scientist,Los Alamos National Laboratory(LANL)LA-UR-23-302732|2023 Triad National Security,LLC.All Rights Reserved.A Co

2、llaboration with SK hynix3|2023 Triad National Security,LLC.All Rights Reserved.ProblemScientific data analytics often slowed down by unordered,unindexed data accessKV-CSDAn ordered,hardware-accelerated KV store for rapid data insertion and queriesGoalLeverage computational storage to sort and index

3、 data at restOverview4|2023 Triad National Security,LLC.All Rights Reserved.A Quick LookThe arm board implements KV atop SSD zonesApps use custom NVMe KV commands for bulk data insertion,index creation,and queriesAppArm SoC boradZNS SSDTwo components:(1)an arm SoC board,(2)a ZNS SSDKV5|2023 Triad Na

4、tional Security,LLC.All Rights Reserved.KV-CSD in Real WorldCurrent PrototypeZNS SSDARM SoC(FPGA in future)PCIe(NVMeOF in future)ZNS SSDARM SoC 6|2023 Triad National Security,LLC.All Rights Reserved.Why ordered computational KV storage?How does it work?Todays Talk7|2023 Triad National Security,LLC.A

5、ll Rights Reserved.How Scientific Simulations RunTime based bulk-synchronous parallel programsIterate between compute&I/O phasesAnalytics occur after simulationCompute IO Compute IO Compute IOAnalyticsSimulation PipelineTimeTimestep 0-15Timestep 16-31Timestep 32-47Persist timestep 15 to storage8|202

6、3 Triad National Security,LLC.All Rights Reserved.How Data is Stored TodayThrough filesystemsData stored as one big or many small files per timestepData typically accompanied by metadata that describes the data(type,dimension,)Compute IO Compute IO Compute IOAnalyticsSimulation PipelineTimeFilesFile

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本文介绍了一种名为KV-CSD的新型有序、硬件加速的键值存储解决方案,由美国洛斯阿拉莫斯国家实验室的科学家Qing Zheng及其团队开发。该技术旨在解决科学数据分析中因无序、未索引数据访问而导致的缓慢问题。KV-CSD通过在存储设备内排序数据并建立索引,实现了快速的数据插入和查询。其核心组件包括基于ARM的SoC板和ZNS SSD,通过定制NVMe KV命令实现数据处理。实验结果显示,KV-CSD在数据插入和范围查询方面显著优于传统的软件键值存储解决方案,如RocksDB,它通过硬件加速有效隐藏了后台工作的延迟,并在查询性能上实现了7.4倍的提升。这一突破性的技术已获得研发100奖,并在2023年的Flash Memory Summit上进行了演示。
"KV-CSD如何提高科学数据分析效率?" "硬件加速如何改变科学数据存储与查询?" "KV存储在科学计算中的应用前景如何?"
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