Kirk E. Jordan, Ph.D.

Emerging Solutions Executive
Deep Computing
IBM Systems and Technology Group

Presentation

High Performance Computing Simulations Enable Breakthroughs in Science and Engineering

High performance computing (hpc) is a tool frequently used to understand complex problems in numerous areas such as aerospace, biology, climate modeling and energy. Scientists and engineers working on problems in these and other areas demand ever increasing compute power for their problems. In order to satisfy the demand for increase performance to achieve breakthrough science and engineering, we turn to parallelism through large systems with multi-core chips. Through the combination of hpc hardware coupled with novel algorithmic approaches, some efforts toward breakthroughs in science and engineering are described. While progress is being made, there remain many challenges for the computational science community to apply ultra-scale systems and multi-core systems to "Big" science problems with impact on society that until now or in current implementations have fallen short of the mark. In conclusion, some discussion not only on the most obvious way to use ultra-scale hpc systems will be given but also some thoughts on how one might use such systems to tackle previously intractable problems.

Biography

Dr. Kirk E. Jordan, Emerging Solutions Executive in IBM Deep Computing, has more than 25 years experience in high performance and parallel computing. In Deep Computing, he oversees development of applications for IBM's advanced computing architectures, investigates and develops concepts for new areas of growth especially in the life sciences involving high performance computing (HPC), and provides leadership in high-end computing and simulation in such areas as systems biology and high-end visualization. At IBM, he held several positions promoting HPC and high performance visualization, including managing IBM's University Relations SUR (Shared University Research) Program and leading IBM's Healthcare and Life Sciences Strategic Relationships and Institutes of Innovation Programs. A Ph.D. in Applied Math, he held computational science positions at Exxon R&E, Argonne National Lab, Thinking Machines and Kendall Square Research before joining IBM in 1994. A Research Affiliate in MIT's Department of Aeronautic and Astronautics, he holds leadership positions in the Society for Industrial and Applied Mathematics (SIAM), including Secretary of Computational Science and Engineering SIAG and the Committee on Science Policy. He is on several boards including Math Biosciences Institutes Scientific Advisory Board and Board of Trustees at The Ohio State University and the International Advisory Board for the Systems Biomedicine Institute at Shanghai Jaio Tong University. He is associate editor of several international journals and Guest Editor for two recent issues of IBM's Journal for Research and Development.

updated: 2008-10-07