High Performance Scientific Computing PPT


Thoughts on High Performance Computing: from 1989 till the present and beyond

I have been involved in technical computing for over 40 years, starting with minicomputers that were used by this community. This is a collection of articles, memos, talks, and testimony covering that period.

  • (2.5 PPT). Talk given at the 100th Centenary of John Vincent Atanasoff at Iowa State University on 30 October-November 1 at their Symposium on Modern Computing. This talk is substantially along the lines of my criticism of the U.S. efforts to regain supremacy for the world's fastest computer from Japan. Our approach that uses loosely coupled, commodity-based uni- and multi-processor computers is still not a match for a very high speed cross-point switch interconnecting shared memory vector processors that NEC has evolved based on the "Cray" formulae.
  • Global Grid Forum Keynote 25 June 2003, Seattle. Basic messages using six examples: enable your applications now as web services, Grid developers need to adopt users in order to understand how to create the Grid, and we see a real drive to Community and Data Centric Computing. This new world will be around databases and data mining where discoveries come from analyzing large datasets. Over time, the web services program model may be so pervasive, that these services will be the way to communicate within the computer. Furthermore, web services begin to open up the 20 year promise of distributed computing.
  • DOE Science Computing Conference 2003 19 June 2003 includes my talk entitled Seven Paths to High Performance (and the Petaflops) . Evolution is the most likely path. Any idea of a magic bullet that will not be tried by Moore's Law is fool-hearty. The DARPA HPC program is certain to require more than six years to achieve any significant performance. The tried and true vector architecture with tight coupling among nodes must remain as a component as the Japanese have shown in their use at NEC and Fujitsu -and especially their compilers. Finally, we must go back and work on the programming environment for cluster that includes both the compiler and run-time systems.

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