Wenji Wu
An expert in both quantum and classical networks, Dr. Wenji Wu is a network research engineer in Lawrence Berkeley National Laboratory's Scientific Networking Division, where he works on quantum networks, high-speed networking, and distributed systems for QUANT-NET and for ESnet's Testbeds & Prototypes group.
Dr. Wu is the PI on two DOE network research projects, the MDTM project and the BigData Express project. These two projects are targeted at providing schedulable, predictable, and high-performance data transfer service for DOE’s large-scale science computing facilities and their collaborators.
His recent research focuses on quantum networks. He is currently working on the QUANT-NET project, which aims to build a three-node quantum network testbed in Berkeley area. His roles in the project are (1) quantum network architecture and protocol stack research and development and (2) quantum network real-time control system research and development.
Dr. Wu earned his Ph.D. in computer engineering from University of Arizona.
Journal Articles
Syed Asif Raza, Wenji Wu, Qiming Lu, Liang Zhang, Sajith Sasidharan, Phil DeMar, Chin Guok, John Macauley, Eric Pouyoul, Jin Kim, Seo-Young Noh, “AmoebaNet: An SDN-enabled network service for big data science”, Journal of Network and Computer Applications, Elsevier, October 1, 2018, 119:70-82,
Liang Zhang, Wenji Wu, Phil DeMar, “mdtmFTP and its evaluation on ESNET SDN testbed”, Future Generation Computer Systems, Elsevier, February 1, 2018, 79:199-204,
Wenji Wu, Phil DeMar, Matt Crawford, “A transport-friendly NIC for multicore/multiprocessor systems”, IEEE Transactions on Parallel and Distributed Systems, July 14, 2011, 23:607-615,
Wenji Wu, Phil DeMar, Matt Crawford, “Why can some advanced Ethernet NICs cause packet reordering?”, IEEE Communications Letter, February 1, 2011, 15:253-255,
Wenji Wu, Phil DeMar, Matt Crawford, “Sorting reordered packets with interrupt coalescing”, Computer Networks, Elsevier, October 12, 2009, 53:2646-2662,
Wenji Wu,Matt Crawford,Mark Bowden, “The performance analysis of Linux networking–packet receiving”, Computer Communication, Elsevier, March 8, 2007, Volume 3:1044-1057,
Wenji Wu, Matt Crawford, “Potential performance bottleneck in Linux TCP”, International Journal of Communication Systems, Wiley, February 1, 2007, 20:1263-1283,
Conference Papers
Inder Monga, Erhan Saglamyurek, Ezra Kissel, Hartmut Haffner, Wenji Wu, “QUANT-NET: A testbed for quantum networking research over deployed fiber”, SIGCOMM QuNet'23, ACM, September 10, 2023, QuNet'23:31-37,
Wenji Wu, Joaquin Chung, Gregory Kanter, Nikolai Lauk Raju Valivarthi, Russell Ceballos, Cristian Pena, Neil Sinclair, Jordan Thomas, Ely Eastman, Si Xie, Rajkumar Kettimuthu, Prem Kumar, Panagiotis Spentzouris, Maria Spiropulu, “Illinois express quantum network for distributing and controlling entanglement on metro-scale”, IEEE/ACM International Workshop on Quantum Computing Software (QCS), IEEE/ACM, December 22, 2021,
Joaquin Chung, Gregory Kanter, Nikolai Lauk, Raju Valivarthi, Wenji Wu, Russell R. Ceballos, Cristián Peña, Neil Sinclair, Jordan Thomas, Si Xie, Rajkumar Kettimuthu, Prem Kumar, Panagiotis Spentzouris, Maria Spiropulu, “Illinois Express Quantum Network (IEQNET): metropolitan-scale experimental quantum networking over deployed optical fiber”, SPIE, Quantum Information Science, Sensing, and Computation XIII, SPIE, April 21, 2021,
Wenji Wu, Liang Zhang, Qiming Lu, Phil DeMar, Robert Illingworth, Joe Mambretti, Se-Young Yu, Jim Hao Chen, Inder Monga, Xi Yang, Tom Lehman, Chin Guok, John MacAuley, “ROBIN (RuciO/BIgData Express/SENSE) A Next-Generation High-Performance Data Service Platform”, 2020 IEEE/ACM Innovating the Network for Data-Intensive Science (INDIS), IEEE/ACM, December 31, 2020,
Qiming Lu, Liang Zhang, Sajith Sasidharan, Wenji Wu, Phil DeMar, Chin Guok, John Macauley, Inder Monga, Se-Young Yu, Jim Hao Chen, Joe Mambretti, Jin Kim, Seo-Young Noh, Xi Yang, Tom Lehman, Gary Liu, “BigData Express: Toward Schedulable, Predictable, and High-Performance Data Transfer”, 2018 IEEE/ACM Innovating the Network for Data-Intensive Science (INDIS), IEEE/ACM, February 24, 2019,
Liang Zhang, Phil Demar, Bockjoo Kim, Wenji Wu, “MDTM: Optimizing Data Transfer Using Multicore-Aware I/O Scheduling”, 2017 IEEE 42nd Conference on Local Computer Networks (LCN), IEEE, September 12, 2017,
Bulk data transfer is facing significant challenges in the coming era of big data. There are multiple performance bottlenecks along the end-to-end path from the source to destination storage system. The limitations of current generation data transfer tools themselves can have a significant impact on end-to-end data transfer rates. In this paper, we identify the issues that lead to underperformance of these tools, and present a new data transfer tool with an innovative I/O scheduler called MDTM. The MDTM scheduler exploits underlying multicore layouts to optimize throughput by reducing delay and contention for I/O reading and writing operations. With our evaluations, we show how MDTM successfully avoids NUMA-based congestion and significantly improves end-to-end data transfer rates across high-speed wide area networks.
