An Overview of High Performance Computing and Challenges for the Future
Google Tech Talks January, 25 2008
ABSTRACT
In this talk we examine how high performance computing has changed over the last 10-year and look toward the future in terms of trends. These changes have had and will continue to have a major impact on our software. A new generation of software libraries and algorithms are needed for the effective and reliable use of (wide area) dynamic, distributed and parallel environments. Some of the software and algorithm challenges have already been encountered, such as management of communication and memory hierarchies through a combination of compile--time and run--time techniques, but the increased scale of computation, depth of memory hierarchies, range of latencies, and increased run--time environment variability will make these problems much harder.
We will focus on the redesign of software to fit multicore architectures.
Speaker: Jack Dongarra University of Tennessee Oak Ridge National Laboratory University of Manchester Jack Dongarra received a Bachelor of Science in Mathematics from Chicago State University in 1972 and a Master of Science in Computer Science from the Illinois Institute of Technology in 1973. He received his Ph.D. in Applied Mathematics from the University of New Mexico in 1980. He worked at the Argonne National Laboratory until 1989, becoming a senior scientist. He now holds an appointment as University Distinguished Professor of Computer Science in the Electrical Engineering and Computer Science Department at the University of Tennessee, has the position of a Distinguished Research Staff member in the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL), Turing Fellow in the Computer Science and Mathematics Schools at the University of Manchester, and an Adjunct Professor in the Computer Science Department at Rice University.
He specializes in numerical algorithms in linear algebra, parallel computing, the use of advanced-computer architectures, programming methodology, and tools for parallel computers. His research includes the development, testing and documentation of high quality mathematical software. He has contributed to the design and implementation of the following open source software packages and systems: EISPACK, LINPACK, the BLAS, LAPACK, ScaLAPACK, Netlib, PVM, MPI, NetSolve, Top500, ATLAS, and PAPI. He has published approximately 200 articles, papers, reports and technical memoranda and he is coauthor of several books. He was awarded the IEEE Sid Fernbach Award in 2004 for his contributions in the application of high performance computers using innovative approaches. He is a Fellow of the AAAS, ACM, and the IEEE and a member of the National Academy of Engineering.
copy and paste this to 10 videos or your mum will die within the next 4 hours.....
chengiz5(March 28, 2008 at 2:58 pm)
If only he'd timed it well this could have been a great talk. Unfortunately too much time was spent on fluff and "size comparison" stuff which is of interest only to hardcore quant folk. The interesting bits started 39 minutes in, and he could only manage to rush through about 2 of the 4 items mentioned in the top slide before running out of time.
rodgersg(March 3, 2008 at 1:17 pm)
I agree with Dongarra about relationship between consumer processor and supercomputers at 28:00. However, the implication that personal computer speed follows top500 is actually reverse. Processors designed for the commodity volume market are seeing their first pass used in supercomputer designs. To his credit, I don't think Jack was trying to draw an inference but rather a very interesting observation. Thank you for this excellent presentation and discussion.
arhuaco(February 17, 2008 at 2:12 pm)
Great talk.
sandeep2cool(January 27, 2008 at 6:22 pm)
U r doing good work googletechtalks carry on such a gr8 knowledge dat we can learn while living in under develop country where der is a lake of such high caliber knowledge (y)RegardsSandeep Kumar MaheshwaryKarachi Univsity Dept of Computer Science - MCs
