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Tong Zhang

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titleconferencedate
HaSiS: A Hardware-assisted Single-index Store for Hybrid Transactional and Analytical...FAST '252025-02-25
A B+-tree single-index store leverages commercially available computational storage drives with transparent compression to run HTAP without dual indexes. The…
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Closing the B+-tree vs. LSM-tree Write Amplification Gap on Modern Storage Hardware...FAST '222022-02-22
Shows three concrete changes — deterministic page shadowing, localized modification logging, and sparse redo logging — applied to a B+-tree implementation and…
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Postgres Meets Computational StorageFOSDEM 20212021-02-06
Higher Performance at Lower Cost This proposed talk will present how Postgres could seamlessly and significantly benefit from replacing normal solid-state…
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How Can Databases Capitalize on Computational Storage?Percona Live Online 20202020-10-20
ScaleFlux CSD 2000 drives run compression and other compute in-drive so MySQL and Postgres see about 2x throughput versus NVMe with host compression while…
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Re-think Data Management Software Design Upon the Arrival of Storage Hardware with12th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage '20)2020-07-13
Argues that transparent compression embedded in drives (an FPGA-based flash controller exposing a standard block device) decouples logical from physical…
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Re architecting Congestion Management in Lossless EthernetNSDI 20202020-02-25
Claims that existing lossless Ethernet congestion control fails because congestion detection and rate adjustment are ineffective and replaces them with…
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POLARDB Meets Computational Storage: Efficiently Support Analytical Workloads in CloudFAST '202020-02-24
Paper reports a deployed replacement of SSDs with FPGA-based computational storage drive devices inside Alibaba Cloud POLARDB, plus coordinated changes to the…
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Stochastic Optimization for Big Data Machine Learning ProblemsParallel and Distributed Algorithms for Inference and Optimization (Simons Institute, Oct. 21–24, 2013)2013-10-21
Claims that SVRG and SDCA fix SGD by eliminating gradient variance and deliver linear convergence while touching one example per iteration, so per-iteration…
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