"High Performance Computing, Now and in the Future" by Olaf O. Storaasli Distinguished Research Scientist Future Technologies Group Computational Sciences Directorate Oak Ridge National Laboratory When I performed Structural Analysis Computations at NASA Langley in the 70's people were astounded by our achievment of Millions of FLoating Point Operations/Sec (MFLOPS), truly High_performance Computing, then. Not until 1989, was the next level of performance (1000 MFLOPS) achieved by a NASA-ODU team (Storaasli-Nguyen-Agarwal) who received Cray's 1st GigaFLOP Award (1 billion FLoating Point Operations/Sec) who achieved 1.334 GFLOPS performance for the static analysis of a "gigantic" Space Shuttle Solid Rocket Booster with 54K equations. In 1998 another Cray T3E at ORNL broke the TeraFLOP (1,000,000 MFLOPS). Not until 2008 did DOE computers (at LANL and ORNL) exceed 1 PetaFLOP (1,000,000,000 MFLOPS), a billion times faster than the early NASA computers. See details on ORNL's Jaguar at: http://www.energy.gov/discovery/the_supercomputing_fast_lane.html DOE views Supercomputers as the 3rd leg of scientific discovery along with theory and experiment and that an increasing number of significant discoveries will be performed on supercomputers. Dr Storaasli will describe the current top fleet of supercomputers (mostly DOE), what they consist of (hardware and software), and what applications they solve. In addition, based on his research in the Future Technologies Group at ORNL, Dr. Storaasli will project what the next level of supercomputers (ExaFLOP) will look, including their architecture, software, tools and applications and what performance levels they will achieve. Dr. Storaasli is an internationally-known expert on parallel methods for computational analysis on High-Performance Computers (HPC) having conducted research in this area for over thirty years. Before parallel computers were sold, Dr. Storaasli led a NASA hardware-software-applications team to develop the Finite Element Machine (Wikipedia), one of the 1st parallel computers. As a NASA senior computational scientist, his research developed new parallel algorithms to solve large systems of matrix equations for aerospace structures, electromagnetic and acoustic applications. These were first developed to harness cutting-edge NASA supercomputers (1st Cray GigaFLOP award and NASA Software of the Year Award), then parallel computers and recently even faster accelerators sped by Field-Programmable Gate Arrays (FPGAs). At NASA he edited six books and authored over 100 works in computational mechanics including static and dynamic structural analysis, eigenvalue & optimization methods, interdisciplinary analysis, data management, and parallel-vector structural analysis methods on supercomputers. He received NASA.s prestigious Floyd Thompson Fellowship for post-doctoral research at the Norwegian University of Science & Technology in Trondheim and Det Norske Veritas in Oslo, Norway, in 1984-85. He has been invited to give dozens of HPC lectures including 16 overseas. He conceived and led a NASA Creativity and Innovation team to explore FPGAs as an alternative to traditional processors to accelerate scientific and engineering computing. This led to NASA.s $15M award for his reconfigurable scalable FPGA computer project for space applications (image compression and robotics). Current Assignment Dr. Storaasli joined ORNL.s Computer Science & Mathematics Division.s Future Technologies Group in 2005 to explore new algorithms-architectures to accelerate scientific supercomputing by harnessing FPGAs. His research evaluated multiple FPGA systems at ORNL(6), Cray(6), Edinburgh University (64) and the Naval Research Lab (150). Speedups of 10-100X over traditional processors resulted for key Department of Energy (DOE) analyses (climate/weather, molecular dynamics, genomics, large matrix equation solution). His research spun off DOE (Science Alliance and SBIR) and USAF research awards. Dr. Storaasli currently leads a cross-cutting ORNL team planning to apply rapid FPGA genomics to future low-cost personalized medicine.