Keynotes

Keynote New Datacenter Architecture with Utilization and QoS for Big Data Processing
Speaker Minyi Guo, Shanghai Jiao Tong University
Abstract Nowadays, sensing technologies and large-scale computing infrastructures have produced a variety of big data in urban spaces, e.g. human mobility, air quality, traffic patterns, and geographical data. The big data implies rich knowledge about a city and can help tackle these challenges when used correctly. That is, holistic urban big data plays the key role in smart city constructions. However, processing urban big data needs the specific computing engine different with traditional one such as Hadoop and Spark, because the sensing and knowledge representation are more complicated than domain-specific big data. In this talk, we will give some properties for processing big data and introduce a new platform for processing and analyzing urban big data. Then we discuss some techniques for new datacenter architectures to improve utilization while guaranteeing QoS of lantency-sensitive applications.
Short Bio minyi guo

Minyi Guo received the BSc and ME degrees in computer science from Nanjing University, China; and the PhD degree in computer science from the University of Tsukuba, Japan. He is currently Zhiyuan Chair professor and head of the Department of Computer Science and Engineering, Shanghai Jiao Tong University (SJTU), China. Before joined SJTU, Dr. Guo had been a professor of the school of computer science and engineering, University of Aizu, Japan. Dr. Guo received the national science fund for distinguished young scholars from NSFC in 2007, and was supported by “Recruitment program of Global Experts” in 2010. His present research interests include parallel/distributed computing, compiler optimizations, embedded systems, pervasive computing, big data and cloud computing. He has more than 400 publications in major journals and international conferences in these areas. He received 5 best paper awards from international conferences. He is now on the editorial board of IEEE Transactions on Parallel and Distributed Systems, IEEE Transactions on Cloud Computing and Journal of Parallel and Distributed Computing. Dr. Guo is a fellow of IEEE, and a fellow of CCF.
Keynote ShenTu: Processing Multi-Trillion Edge Graphs on Millions of Cores in Seconds
Speaker Wenguang Chen, Tsinghua University
Abstract Graphs are an important abstraction used in many scientific fields. With the magnitude of graph-structured data constantly increasing, effective data analytics requires efficient and scalable graph processing systems. Although HPC systems have long been used for scientific computing, people have only recently started to assess their potential for graph processing, a workload with inherent load imbalance, lack of locality, and access irregularity. We propose ShenTu, the first general- purpose graph processing framework that can efficiently utilize an entire Petascale system to process multi-trillion edge graphs in seconds. ShenTu embodies four key innovations: hardware spe- cialization, supernode routing, on-chip sorting, and degree-aware messaging, which together enable its unprecedented performance and scalability. It can traverse a record-size 70-trillion-edge graph in seconds. ShenTu enables the processing of internet scale web graphs and shows potential for brain simulation.
Short Bio wenguang chen

Wenguang Chen is a professor in Department of Computer Science and Technology, Tsinghua University. His research interest is in parallel and distributed systems and programming systems. He received the Bachelor’s and Ph.D. degrees in computer science from Tsinghua University in 1995 and 2000 respectively. Before joining Tsinghua in 2003, he was the CTO of Opportunity International Inc. He was appointed as the associate head of Department of Computer Science and Technology from 2007 to 2014.

He has published over 50 papers in international conferences and journals like OSDI, PLDI, SC, ICS, PPoPP, EuroSys, USENIX ATC, OOPSLA, VLDB and ICSE. He is a distinguished member and distinguished speaker of CCF( China Computer Foundation), an ACM member and a Co-Chair of ACM China Council, and an IEEE member.

His recent research focus on graph processing, and proposed a series of graph processing systems, such as GridGraph(single machine out-of-core), Gemini(distributed memory) and Shentu(supercomputer), with his collaborators to provide fast and efficient graph systems on various platforms.