Date March 3, 2017
Speaker Peter Kogge
University of Notre Dame
Title Big Data, Streaming Graphs, and the Need for Innovations in Architecture
Abstract This talk will start with some insights gleaned from looking at real-world big data problems and how they are affected by architecture. The Emu migrating thread architecture is then introduced and compared. A general template for integrated big graph batch and streaming analytic processing is developed, and key graph operations, especially streaming, listed. A discussion follows on how the Emu architecture meshes well with such a dual-mode computing template, with some specific emphasis on machine learning functions.
Bio Peter M. Kogge received his Ph.D. in EE from Stanford in 1973. From 1968 until 1994 he was with IBM's Federal Systems Division, and was appointed an IBM Fellow in 1993. In August, 1994 he joined the University of Notre Dame as first holder of the endowed McCourtney Chair in Computer Science and Engineering. He has served as both Department Chair and Associate Dean for Research, College of Engineering.  He is an IEEE Fellow, a Distinguished Visiting Scientist at JPL, and a founder and Chief Scientist of Emu Solutions, Inc. His research interests are in massively parallel computing paradigms, processing in memory, and the relationship between massive non-numeric applications, emerging technology, and computer architectures. He holds over 40 patents and is author of two books, including the first text on pipelining. His Ph.D. thesis led to the Kogge-Stone adder used in many microprocessors.  Other projects included EXECUBE - the world's first multi-core processor and first processor on a DRAM chip, the IBM 3838 Array processor which was for a time the fastest floating point machine marketed by IBM, and the IOP - the world’s second multi-threaded parallel processor which flew on every Space Shuttle. In 2008, he led DARPA’s Exascale technology study group, which resulted in a widely referenced report on technologies and architectures for exascale computing, and has had key roles on many other HPC programs. His startup, Emu Solutions, has demonstrated the first scalable system that utilizes mobile threads to attack large-scale big data and big graph problems.  Dr. Kogge has received the Daniel Slotnick best paper award (1994), the IEEE Seymour Cray award for high performance computer engineering (2012), the IEEE Charles Babbage award for contributions to the evolution of massively parallel processing architectures (2014), the IEEE Computer Pioneer award (2015), and the Gauss best paper award for high performance computers (2015).

These seminars supported by the Ming Hsieh Institute.