Zhen Peng
Hi there. I am a Postdoctoral Researcher at Pacific Northwest National Laboratory (PNNL). My mentor is Dr. Gokcen Kestor. I received my Ph.D. from the Department of Computer Science at William & Mary under the supervision of Dr. Bin Ren.
My research interests lie in parallel computing with an emphasis on the design and optimization of parallel solutions for sparse computations and graph-based applications, relevant areas including:
- Parallel Computing
- High Performance Computing
- Compilers
- Deep Neural Network Inference
Before joining William & Mary, I received my bachelor’s and master’s degrees in the Department of Computer Science at Huaqiao University, China in 2013 and 2016, respectively. My master’s research advisor is Dr. Tian Wang.
My full CV.
Publications
- [PACT-2023] Zhen Peng, Rizwan A. Ashraf, Luanzheng Guo, Ruiqin Tian, and Gokcen Kestor, “Automatic Code Generation for High-Performance Graph Algorithms,” The 32nd International Conference on Parallel Architectures and Compilation Techniques (PACT ‘23), October 21-25, 2023, Vienna, Austria. [PDF]
- [PPoPP-2023] Zhen Peng, Minjia Zhang, Kai Li, Ruoming Jin, and Bin Ren, “iQAN: Fast and Accurate Vector Search with Efficient Intra-Query Parallelism on Multi-Core Architectures,” The 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming (PPoPP ‘23), February 25-March 1, 2023, Montreal, Canada. [PDF] [SupplementalMaterial]
- [arXiv-2022] Zhen Peng, Minjia Zhang, Kai Li, Ruoming Jin, and Bin Ren, “Speed-ANN: Low-Latency and High-Accuracy Nearest Neighbor Search via Intra-Query Parallelism,” arXiv:2201.13007, 2022. [PDF]
- [TACO-2021] Qihan Wang, Zhen Peng, Bin Ren, Jie Chen, and Robert G. Edwards, “MemHC: An Optimized GPU Memory Management Framework for Accelerating Many-body Correlation,” ACM Transactions on Architecture and Code Optimization (TACO), 2021. [PDF]
- [ICS-2020] Ruoming Jin*, Zhen Peng*, Wendell Wu, Feodor Dragan, Gagan Agrawal, and Bin Ren, “Parallelizing Pruned Landmark Labeling: Dealing with Dependencies in Graph Algorithms,” The 34th ACM International Conference on Supercomputing (ICS ‘20), June 29-July 2, 2020, Online. (* Equal contribution) [PDF] [SupplementalMaterial] [FullTalk]
- [CGO-2020] Yu Chen, Ivy Peng, Zhen Peng, Xu Liu, and Bin Ren, “ATMem: Adaptive Data Placement in Graph Applications on Heterogeneous Memories,” International Symposium on Code Generation and Optimization (CGO ‘20), February 22-26, 2020, San Diego, CA, USA. [PDF]
- [arXiv-2019] Ruoming Jin, Zhen Peng, Wendell Wu, Feodor Dragan, Gagan Agrawal, and Bin Ren, “Pruned Landmark Labeling Meets Vertex Centric Computation: A Surprisingly Happy Marriage!” arXiv:1906.12018, 2019. [PDF]
- [PACT-2018] Zhen Peng, Alexander Powell, Bo Wu, Tekin Bicer, and Bin Ren, “GraphPhi: Efficient Parallel Graph Processing on Emerging Throughput-oriented Architectures,” International conference on Parallel Architectures and Compilation Techniques (PACT ‘18), November 1-4, 2018, Limassol, Cyprus. [PDF] [LightningTalk]
Experience
- 04/2023 - Present, Postdoctoral Researcher, Pacific Northwest National Laboratory (PNNL), Richland, WA
- 06/2022 - 04/2023, PhD Intern, Pacific Northwest National Laboratory (PNNL), Richland, WA
- 04/2021 - 09/2021, Software Engineering Intern, Kuaishou, Palo Alto, CA
- 08/2017 - 06/2022, Research Assistant, College of William & Mary (W&M), Williamsburg, VA