Jiawen Liu


PhD Student, EECS

University of California, Merced

Email: jliu265@ucmerced.edu


Biography

I'm a third year Ph.D. student at UC Merced supervised by Prof. Dong Li. My research interests mainly focus on computer system, machine learning, and high performance computing with a target on building high-performance and resource-aware systems for machine learning.


Recent News

03/2020: One paper, "RIANN: Real-time Incremental Learning with Approximate Nearest Neighbor on Mobile Devices", is accepted in USENIX OpML'20.
02/2020: One paper, "Flame: A Self-Adaptive Auto-Labeling System for Heterogeneous Mobile Processors", is accepted in MLSys-W'20.
09/2019: One paper, "Performance Analysis and Characterization of Training Deep Learning Models on Mobile Device", is accepted in ICPADS'19.
03/2019: Receive IEEE Travel Award from Technical Committee on Parallel Processing (TCPP) for IPDPS'19.
01/2019: One paper, "Runtime Concurrency Control and Operation Scheduling for High Performance Neural Network Training",is accepted in IPDPS'19.
10/2018: Receive ACM/IEEE Travel Award from Advanced Computing Systems Association (USENIX) for OSDI'18.
09/2018: Receive ACM/IEEE Travel Award from National Science Foundation (NSF) for MICRO'18.
08/2018: One paper, "Processing in Memory for Energy-efficient CNN Training: A Heterogeneous Approach", is accepted in MICRO'18.
05/2018: Start summer research intern at Oak Ridge National Laboratory (ORNL).
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Publications


RIANN: Real-time Incremental Learning with Approximate Nearest Neighbor on Mobile Devices
Jiawen Liu, Zhen Xie, Dimitrios Nikolopoulos, Dong Li
USENIX Conference on Operational Machine Learning (USENIX OpML), 2020.


Flame: A Self-Adaptive Auto-Labeling System for Heterogeneous Mobile Processors
Jiawen Liu, Jie Liu, Zhen Xie, Dong Li
On-Device Intelligence Workshop at Machine Learning and Systems Conference (MLSys-W), 2020.


Runtime Concurrency Control and Operation Scheduling for High Performance Neural Network Training
Jiawen Liu, Dong Li, Gokcen Kestor, Jeffrey Vetter
IEEE 33rd International Parallel and Distributed Processing Symposium (IPDPS), 2019. (Acceptance rate: 103/372=27%)


Performance Analysis and Characterization of Training Deep Learning Models on Mobile Device
Jie Liu, Jiawen Liu, Wan Du, Dong Li
IEEE 25th International Conference on Parallel and Distributed Systems (ICPADS), 2019. (Acceptance rate: 97/346=28%)


Processing in Memory for Energy-efficient CNN Training: A Heterogeneous Approach
Jiawen Liu, Hengyu Zhao, Matheus A. Ogleari, Dong Li, Jishen Zhao
IEEE/ACM 51st International Symposium on Microarchitecture (MICRO), 2018. (Acceptance rate: 74/348=21%)


HOMP: Automated Distribution of Parallel Loops and Data in Highly Parallel Accelerator-Based Systems
Yonghong Yan, Jiawen Liu, Kirk Cameron, Mariam Umar
IEEE 31st International Parallel and Distributed Processing Symposium (IPDPS), 2017. (Acceptance rate: 116/516=22%)


Awards

2019               IEEE Travel Award for IPDPS 2019, Technical Committee on Parallel Processing (TCPP)
2018               ACM/IEEE Travel Award for OSDI 2018, Advanced Computing Systems Association (USENIX)
2018               ACM/IEEE Travel Award for MICRO 2018, National Science Foundation (NSF)
2017-2018     Bobcat Research Fellowship, UC Merced
2017               ACM/IEEE Travel Award for SC 2017, Supercomputing (SC)
2017               IEEE Travel Award for IPDPS 2017, Technical Committee on Parallel Processing (TCPP)
2017-Now      Graduate Research Assistantship, UC Merced

Teaching

Spring 2019: CSE179 - Introduction to Parallel Computing

Professional Activities

External reviewers: IPDPS'20, TACO’19, ICPP’19, Cluster’19, NPC’19, SC’18, CCGrid’17, ISCHPC’16, PMAM’16, etc.

Work Experience

Summer 2018: Research intern at Oak Ridge National Laboratory (ORNL)


Last updated on 03/2020.