|Date||November 10, 2016|
University of California, Los Angeles
|Title||Customizable Computing at Datacenter Scale|
|Abstract||Customizable computing has been of interest to the research community for over three decades. The interest has intensified in the recent years as the power and energy become a significant limiting factor to the computing industry. For example, the energy consumed by the datacenters of some large internet service providers is well over 109 Kilowatt-hours. FPGA-based acceleration has shown 10-100X performance/energy efficiency over the general-purpose processors in many applications. With Intel's $17B acquisition of Altera completed in December 2015, customizable computing is going from advanced research projects into mainstream computing technologies.
In this talk, I shall first present evaluation of several CPU+FPGA platforms for datacenter level integration, and the acceleration results in multiple application domains, including medical imaging, machine learning, and computational genomics. Programming effort remains to be a serious challenge. So, the second part of my talk discusses our ongoing effort in automating compilation with source-code level transformation and optimization coupled with high-level synthesis, as well as developing efficient runtime support for scheduling and transparent resource management for integration of FPGAs for cloud-scale acceleration.
|Bio||Jason Cong received his B.S. degree in computer science from Peking University in 1985, his M.S. and Ph. D. degrees in computer science from the University of Illinois at Urbana-Champaign in 1987 and 1990, respectively. Currently, he is a Chancellor's Professor at the UCLA Computer Science Department, the director of Center for Customizable Domain-Specific Computing (CDSC). He served as the department chair from 2005 to 2008. Dr. Cong's research interests include electronic design automation, energy-efficient computing, customized computing for big-data applications, and highly scalable algorithms. He has over 400 publications in these areas, including 10 best paper awards, and the 2011 ACM/IEEE A. Richard Newton Technical Impact Award in Electric Design Automation. He was elected to an IEEE Fellow in 2000 and ACM Fellow in 2008. He received the 2010 IEEE Circuits and System (CAS) Society Technical Achievement Award "For seminal contributions to electronic design automation, especially in FPGA synthesis, VLSI interconnect optimization, and physical design automation" and the 2016 IEEE Computer Society Technical Achievement Award "For setting the algorithmic foundations for high-level synthesis of field programmable gate arrays". He is the only one who received a Technical Achievement Award from both the IEEE Circuits and Systems Society and the Computer Society.
Dr. Cong has graduated 34 PhD students. Nine of them are now faculty members in major research universities, including Cornell, Fudan Univ., Georgia Tech., Peking Univ., Purdue, SUNY Binghamton, UCLA, UIUC, and UT Austin. One of them is now an IEEE Fellow, six of them got the highly competitive NSF Career Award, and one of them received the ACM SIGDA Outstanding Dissertation Award. Dr. Cong has successfully co-founded three companies with his students, including Aplus Design Technologies for FPGA physical synthesis and architecture evaluation (acquired by Magma in 2003, now part of Synopsys), AutoESL Design Technologies for high-level synthesis (acquired by Xilinx in 2011), and Neptune Design Automation for ultra-fast FPGA physical design (acquired by Xilinx in 2013). Currently, he is a co-founder and the chief scientific advisor of Falcon Computing Solutions, a startup dedicated to enabling FPGA-based customized computing in data centers.
These seminars supported by the Ming Hsieh Institute.