Minhui Xie

Ph.D. Student

Storage Research Group

Department of Computer Science and Technology

Tsinghua University

Room 8-201, East Main Building, Tsinghua University, Beijing, China

Email: xmh19 AT mails dot tsinghua dot edu dot cn

About Me

I am Minhui Xie, a third-year Ph.D. student from Tsinghua University. I am a system researcher. My research focus is building efficient systems for at-scale machine learning, with emerging hardware (e.g., persistent memory, modern GPUs). I am so excited about the interact field between ML and System.

Education

Ph.D.

Department of Computer Science, Tsinghua University

2019 - present

B.S.

Department of Computer Science, Nanjing University
GPA 4.84/5.00
Rank 1st /160 (core courses), 3rd /160 (all courses)

2015 - 2019

Publication Lists

  • Pacman: An Efficient Compaction Approach for Log-Structured Key-Value Store on Persistent Memory.
    Jing Wang, Youyou Lu, Qing Wang, Minhui Xie, Keji Huang, Jiwu Shu,
    USENIX Annual Technical Conference (USENIX ATC'22), 2022
    PDF
  • Fleche: An Efficient GPU Embedding Cache for Personalized Recommendations.
    Minhui Xie, Youyou Lu, Jiazhen Lin, Qing Wang, Jian Gao, Kai Ren, Jiwu Shu,
    The 17th European Conference on Computer Systems (EuroSys'22), 2022
    PDF
  • Nap: Persistent Memory Indexes for NUMA Architectures.
    Qing Wang, Youyou Lu, Junru Li, Minhui Xie, Jiwu Shu,
    ACM Transactions on Storage (TOS), 2022
    PDF
  • Kraken: Memory Efficient Continual Learning for Large-Scale Real-Time Recommendations.
    Minhui Xie, Kai Ren, Youyou Lu, Guangxu Yang, Qingxing Xu, Bihai Wu, Jiazhen Lin, Hongbo Ao, Wanhong Xu, Jiwu Shu,
    Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC'20), 2020
    PDF

Projects

Fleche - efficient GPU-resident embedding cache

2021-2021

  • In this work, we identify the DRAM bandwidth scarcity problem and propose Fleche to address it. Fleche’s key idea is absorbing hot accesses via a lightweight GPU-resident embedding cache.
  • Fleche gets up to 4.0x speedup of end-to-end inference throughput than NVIDIA HugeCTR, a well-known highlyoptimized industrial system.
  • It is published in EuroSys’22.

NVMRec - embedding server with byte-addressable non-volatile memory

2019-2020

  • NVMRec is the first system that applies byte-addressable NVM technology for recommendation system in practice. It solves the essential problems caused by poor matching between NVM hardware features and recommendation workloads.
  • It has been deployed at Kuaishou’s datacenters and successfully withstand the access pressure of over 26 billion video recommendations every day. It got 30% cost-savings while maintaining service performance.
  • It has been reported by the industry and official media such as Tsinghua(link), Kuaishou, Intel(link), and People.cn (link).

Kraken - memory efficient continual learning for at-scale recommendation systems

2019-2020

  • Kraken redesigns the age-old structure of embedding tables for continual learning and tailors the optimizer algorithm to make thrift use of DRAM. It can trisect the memory usage while keeping model performance.
  • It has been cited and highly rated by companies including Facebook, Tencent, Alibaba, ByteDance, Kuaishou, and Huawei. It was also incorporated into a popular open-source book on GitHub in the area of MLSys, OpenMLSys (link).
  • It is published in SC’20.

Grants & Awards

Awards During Ph.D.

  • Tsinghua First-class Scholarship

2021

  • Student Grant from USENIX FAST

2021

Selected awards before Ph.D.

  • Outstanding Graduate of Nanjing University

2019

  • Tung OOCL Scholarship (5%)

2018

  • National Scholarship (2%)

2017

  • National Second Prize, China Undergraduate Mathematical Contest in Modeling

2017

  • Meritorious Winner, MCM/ICM

2017

  • Tung OOCL Scholarship (5%)

2016

  • Excellent student at Nanjing University (5%)

2016

Services

  • USENIX ATC 2022, Artifact reviewer
  • OSDI 2022, Artifact reviewer
  • IEEE Transactions on Parallel and Distributed Systems (TPDS), 2022, Reviewer
  • EuroSys 2022, Artifact reviewer
  • Long-term volunteer of ChinaSys

Teaching

  • TA, Computer Organization and Architecture, Tsinghua University, Spring 2022
  • TA, Computer Organization and Architecture, Tsinghua University, Spring 2021
  • TA, Computer Organization and Architecture, Tsinghua University, Spring 2020
  • TA, Introduction to Computer System, Nanjing University, Fall 2017