Biography
I am a research scientist at Meta AI System Co-design. My research interests lie in high performance computing, computer architecture, and machine learning. In particular, my research focuses on building efficient, fast, and scalable systems for machine learning on modern platforms.
My research work has been published in prestigious venues, including ICS, PPoPP, MICRO, ASPLOS, IPDPS, and EuroSys, and receives the ACM ASPLOS Distinguished Artifact Award in 2021.
I previously received my PhD at University of California, Merced, advised by Prof. Dong Li.
Before joining Meta, I worked at Pacific Northwest National Laboratory, Oak Ridge National Laboratory, Tencent America, and Meta.
Selected Publications
Google Scholar
top-cs: top-tier Computer Science publication venue according to CSRankingstop-cr: top-tier Computer Science publication venue according to Conference Ranks
ICS'21
top-cs, top-cr
ICS'21
top-cs, top-cr
PPoPP'21
top-cr
ASPLOS'21
top-cs, top-cr
EuroSys'21
top-cs, top-cr
USENIX OpML'20
RIANN: Real-Time Incremental Learning with Approximate Nearest Neighbor on Mobile Devices
IPDPS'19
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MICRO'18
top-cs, top-cr
IPDPS'17
top-cr
Athena: High-Performance Sparse Tensor Contraction Sequence on Heterogeneous Memory
The 35th ACM International Conference on Supercomputing, 2021. (38/157=24.2%)
Jiawen Liu, Dong Li, Roberto Gioiosa, Jiajia Li
Enabling Energy-Efficient DNN Training on Hybrid GPU-FPGA Accelerators
The 35th ACM International Conference on Supercomputing, 2021. (38/157=24.2%)
Xin He, Jiawen Liu, Zhen Xie, Hao Chen, Guoyang Chen, Weifeng Zhang, Dong Li
Sparta: High-Performance, Element-Wise Sparse Tensor Contraction on Heterogeneous Memory
The 26th ACM Symposium on Principles and Practice of Parallel Programming, 2021. (31/150=20.7%)
Jiawen Liu, Jie Ren, Roberto Gioiosa, Dong Li, Jiajia Li
Fast, Flexible and Comprehensive Bug Detection for Persistent Memory Programs
The 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2021. (75/398=18.8%) (ACM Distinguished Artifact Award)
Bang Di, Jiawen Liu, Hao Chen, Dong Li
Tahoe: Tree Structure-Aware High Performance Inference Engine for Decision Tree Ensemble on GPU
The 16th ACM European Conference on Computer Systems, 2021. (38/191=19.9%)
Zhen Xie, Wenqian Dong, Jiawen Liu, Hang Liu, Dong Li
USENIX Conference on Operational Machine Learning, 2020.
Jiawen Liu, Zhen Xie, Dimitrios Nikolopoulos, Dong Li
Runtime Concurrency Control and Operation Scheduling for High Performance Neural Network Training
The 33rd IEEE International Parallel and Distributed Processing Symposium, 2019. (103/372=27.7%)
Jiawen Liu, Dong Li, Gokcen Kestor, Jeffrey Vetter
Processing in Memory for Energy-Efficient CNN Training: A Heterogeneous Approach
The 51st IEEE/ACM International Symposium on Microarchitecture, 2018. (74/348=21.3%)
Jiawen Liu, Hengyu Zhao, Matheus A. Ogleari, Dong Li, Jishen Zhao
HOMP: Automated Distribution of Parallel Loops and Data in Highly Parallel Accelerator-Based Systems
The 31st IEEE International Parallel and Distributed Processing Symposium, 2017. (116/516=22.5%)
Yonghong Yan, Jiawen Liu, Mariam Umar, Kirk Cameron
Work Experience
- Summer 2021: Tencent America
- Spring 2021: Meta
- Fall 2020: Pacific Northwest National Laboratory (PNNL)
- Summer 2020: Pacific Northwest National Laboratory (PNNL)
- Summer 2018: Oak Ridge National Laboratory (ORNL)
Last updated in 06/2022.
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