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PPoPP 2022
Sat 2 - Wed 6 April 2022
Jidong Zhai

Registered user since Sun 6 May 2018

Name:Jidong Zhai

Jidong Zhai is a Tenured Associate Professor in the Department of Computer Science and Technology of Tsinghua University. He was a Visiting Professor of Stanford University (2015-2016) and a Visiting Scholar of MSRA (Microsoft Research Asia) in 2013. He is the general secretary of ACM SIGHPC China.

His current research interests include parallel computing, compiler, programming language, and performance evaluation. He has published in prestigious conferences (such as SC, ICS, PPOPP, ASPLOS, MICRO, OSDI, ATC, and PACT) and top-tier journals (such as IEEE TC and IEEE TPDS). His research received Best Student Paper Award at ICS’21, Best Paper Honorable Mention Award at ICDCS’20, and Best Paper Finalist at SC’14. He has served as a PC member for a number of international conferences including SC, ICS, PPoPP, IPDPS, ICPP, Cluster, and PACT. He was a program co-chair of NPC 2018. He is currently on the editorial boards of IEEE Transactions on Computers (TC), IEEE Transactions on Parallel and Distributed Systems (TPDS), IEEE Transactions on Cloud Computing (TCC), and Journal of Parallel and Distributed Computing (JPDC).

He is the advisor of Tsinghua Student Cluster Team. The team led by him has achieved 11 international champions in student supercomputing challenges at SC, ISC, and ASC. In 2015 and 2018, the team led by him swept all three champions. He has got a number of awards including CCF outstanding doctoral dissertation Award (2010), NSFC Young Career Award (2017), IEEE TPDS Award for Editorial Excellence (2019), and CCF-IEEE CS Young Computer Scientist Award.

Affiliation:Tsinghua University
Research interests:Parallel Computing, Performance Analysis, Heterogeneous Computing


PPoPP 2022 Publicity Co-Chair (Asia) in Organizing Committee
PerFlow: A Domain Specific Framework for Automatic Performance Analysis of Parallel Applications
FasterMoE: Modeling and Optimizing Training of Large-Scale Dynamic Pre-Trained Models
Vapro: Performance Variance Detection and Diagnosis for Production-Run Parallel Applications
Committee Member in Program Committee
BAGUALU: Targeting Brain Scale Pretrained Models with over 37 Million Cores
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