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Xingda Wei (魏星达)

Assistant Professor
Institute of Parallel And Distributed Systems
School of Software
Shanghai Jiao Tong University
Software Building, 800 Dongchuan Rd., Shanghai, China
Zip/Postal Code: 200240
Email: wxdwfc at sjtu dot edu dot cn (wxdwfc@sjtu.edu.cn)

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About Me

I am an assistant professor in the institute of parallel and distributed systems (IPADS) at Shanghai Jiaotong University (SJTU). My research focuses on improving the performance and reliability for computer systems and distributed systems, particularly how to design systems with emergency hardware technologies and design systems with machine learning technologies.

I am looking for self-motivated students interested in building distributed systems with modern hardware technolgies. Drop me an E-mail if you want to join us!

Research

My research focuses on building fast and reliable distributed systems. I primarily think about the following question: how can we leverage the heterogeneous hardware features in modern datacenters and powerful machine learning technologies to build the next-generation distributed systems? Specifically, I focus on the following topics:

  • How to co-design systems with modern datacenter networking? Modern datacenter fast interconnects like RDMA and SmartNIC offer extremely powerful in-networking computing capabilities. How can we fully utilize the power of these networking features? My related projects include:
  • Machine learning for systems. The advances in machine learning (ML) technologies also bring huge optimization space for computer systems. Besides providing powerful heuristics, the ML methods can change the complexity of traditional algorithms (e.g., sorting and indexing). My related projects include:
    • XStore: Fast RDMA-based Ordered Key-Value Store using Remote Learned Cache [OSDI'20 ACM TOS]
  • Systems with storage class memory. Storage class memory, aka, NVM has finally come to the public market. Besides high performance, its memory-like interfaces give us opportunities to re-think the design of traditional storage systems. My related projects include:
    • Fast remote persistent memory: Characterizing and Optimizing Remote Persistent Memory with RDMA and NVM [USENIX ATC'21]
  • Next-generation cloud computing infrastructure. Serverless computing is a promising future direction for future cloud computing; it has the benefits of auto-scaling and pay-as-you-go, just to name a few. However, current systems have huge performance costs when supporting the above features. How can we build the next-generation serverless system?

Awards and Honors

  • Huawei OlympusMons Pioneer Award, 2020 Link
  • Microsoft Research Asia Fellowship Award, 2018 Link
  • Excellent Bachelor Thesis, 2015

Services

  • JSys Student Editorial Board Link
  • TOCS'20, Reviewer
  • TPDS'20, Reviewer

Publications

2021

  • [USENIX ATC] Xingda Wei, Xiating Xie, Rong Chen, Haibo Chen, Binyu Zang. Characterizing and Optimizing Remote Persistent Memory with RDMA and NVM. 2021 USENIX Annual Technical Conference, July 2021. [paper]
  • [NSDI] Xingda Wei, Rong Chen, Haibo Chen, Zhaoguo Wang, Zhenhan Gong, and Binyu Zang. Unifying Timestamp with Transaction Ordering for MVCC with Decentralized Scalar Timestamp. The 18th USENIX Symposium on Networked Systems Design and Implementation, Boston, MA, US, April 2021. [paper] talk github

2020

  • [OSDI] Xingda Wei, Rong Chen, and Haibo Chen. Fast RDMA-based Ordered Key-Value Store using Remote Learned Cache. 14th USENIX Symposium on Operating Systems Design and Implementation, Banff, Alberta, Canada, November 2020. [paper] talk github
    Full version paper: ACM TOS

2019

  • [USENIX ATC] Xiating Xie, Xingda Wei, Rong Chen, and Haibo Chen. Pragh: Locality-preserving Graph Traversal with Split Live Migration. 2019 USENIX Annual Technical Conference, Renton, WA, US, July 2019. [paper] talk

2018

  • [OSDI] Xingda Wei, Zhiyuan Dong, Rong Chen, and Haibo Chen. Deconstructing RDMA-enabled Transaction Processing: Hybrid is Better! 13th USENIX Symposium on Operating Systems Design and Implementation, Carlsbad, CA, US, October 2018. [paper] [slides] talk github

2017

  • [USENIX ATC] Xingda Wei, Sijie Shen, Rong Chen, and Haibo Chen. Replication-driven Live Reconfiguration for Fast Distributed Transaction Processing. 2017 USENIX Annual Technical Conference, Santa Clara, CA, US, July 2017. [paper]
  • [TOCS] Haibo Chen, Rong Chen, Xingda Wei, Jiaxin Shi, Yanzhe Chen, Zhaoguo Wang, Binyu Zang, Haibing Guan. Fast In-memory Transaction Processing using RDMA and HTM. ACM Transactions on Computer Systems, Vol. 35, No. 1, Article 3, July, 2017. [paper]

2016

  • [EuroSys] Yanzhe Chen, Xingda Wei, Jiaxin Shi, Rong Chen, and Haibo Chen. Fast and General Distributed Transactions Using RDMA and HTM. 11th ACM European Conference on Computer Systems, London, UK, April 2016. [paper] ACM DL

2015

Teaching

pub/members/xingda_wei.txt · Last modified: 2021/09/24 18:09 by weixd