"The Era of Accelerators", Viktor K. Prasanna, University of Southern California

This talk will review the promise of reconfigurable computing leading up to current trends in accelerators. We will illustrate FPGA-based parallel architectures and algorithms for a variety of data analytics kernels in advanced networking, streaming graph processing and machine learning. While demonstrating algorithm-architecture co-design methodology to realize high performance accelerators for deep packet inspection, regular expression matching, packet classification, traffic classification, heavy hitter detection, etc., we demonstrate the role of modeling and algorithmic optimizations to develop highly efficient IP cores. We also show high throughput and energy efficient accelerator designs for a class of graph analytics and machine learning kernels. Our approach is based on high level abstractions of the FPGA platforms and design of efficient data structures, algorithms and mapping methodologies. We conclude by identifying opportunities and challenges in exploiting emerging heterogeneous architectures composed of multi-core processors, FPGAs, GPUs and coherent memory.

Viktor K. Prasanna is Charles Lee Powell Chair in Engineering in the Ming Hsieh Department of Electrical Engineering and Professor of Computer Science at the University of Southern California. He is the Steering Co-chair of the IEEE International Parallel and Distributed Processing Symposium (www.ipdps.org) and the Steering Chair of the IEEE International Conference on High Performance Computing (www.hipc.org). He is a Fellow of the IEEE, the ACM and the American Association for Advancement of Science (AAAS). He is a recipient of 2009 Outstanding Engineering Alumnus Award from the Pennsylvania State University. He received the 2015 W. Wallace McDowell award from the IEEE Computer Society for his contributions to reconfigurable computing.