Colloquium - Hind

The past decades have seen substantial advances in the way programs are developed, thus improving software developers' ability to construct sophisticated applications. Over these same decades computer systems advanced as well, delivering the performance needed to run these complex applications. However, future trends suggest that the complexity of software will continue to increase, yet the performance improvements obtained from processor technology will diminish. This presents a significant challenge and opportunity for the "old" field of software optimization.

In this talk, I will defend why software optimization is important, and argue that today's virtual machines are not making full use of the optimization opportunities available. I will then provide a brief survey of software optimization in virtual machines, debunking several misconceptions about the current field of dynamic optimization, and discussing potential opportunities for moving VM's to the next level of performance.

Michael Hind received his PhD degree from New York University in 1991. From 1992-1998, Michael was an assistant and associate professor of computer science at the State University of New York at New Paltz. In 1998, Michael became a Research Staff Member in the Software Technology Department at the IBM T. J. Watson Research Center, working on the Jalapeno project, the project that produced the open source Jikes RVM. In 2000, he became the manager of the Dynamic Optimization Group at IBM Research. Michael is a member of the Jikes RVM steering committee and core teams. His research interests include adaptive optimization, program analysis, and software optimizations to address memory latency.