BestTechVideos: Tag math Videos

An Overview of High Performance Computing and Challenges for the Future

scoundrel — Fri, 25 Apr 2008 01:40:50 GMT

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.

BestTechVideos: Tag math Videos

An Overview of High Performance Computing and Challenges for the Future

Decayed MCMC for probabilistic filtering

Scene Discovery by Matrix Factorization

Basics of probability and statistic

New generation of math software from Maplesoft

MWRC: Carl Youngblood - Simple Bayesian Networks with Ruby

Supersymmetry, Extra Dimensions and the Origin of Mass

Universal Cache Miss Equations for the Memory Hierarchy

Data Representation/Laplace Operator

Multifractals: The scalability of random multiplicative processes

Discrete Mathematics Lecture 20/20: Cryptography

Discrete Mathematics Lecture 19/20: Recitation - a combinatorial card trick

Discrete Mathematics Lecture 18/20: Euclid's Algorithm

Discrete Mathematics Lecture 17/20: Equivalence Relations and Partial Orders

Discrete Mathematics Lecture 16/20: The pigeonhole principle and examples. The inclusion/exclusion theorem and advanced examples. A combinatorial card trick.

Discrete Mathematics Lecture 15/20: Counting problems using combinations, distributions

Discrete Mathematics Lecture 14/20: Counting problems using combinations, distributions

Discrete Mathematics Lecture 13/20: Counting problems

Discrete Mathematics Lecture 12/20: Counting Problems

Discrete Mathematics Lecture 11/20: Combinations and permutations

Discrete Mathematics Lecture 10/20: Mathematical induction

Discrete Mathematics Lecture 9/20: Solving recurrence equations (cont)

Discrete Mathematics Lecture 8/20: Solving recurrence equations

Discrete Mathematics Lecture 7/20: Chinese rings puzzle

Discrete Mathematics Lecture 6/20: Basic arithmetic and geometric sums, closed forms

Discrete Mathematics Lecture 4/20: Sets

Discrete Mathematics Lecture 3/20: Quantifiers and predicates

Discrete Mathematics Lecture 2/20: Boolean Algebra and formal logic

Discrete Mathematics Lecture 1/20: What kinds of problems are solved in discrete math?

Combining Discriminative Features to Infer Complex Trajectories

On Sequence Kernels for SVM classification of sets of vectors

High Radix Interconnection Networks

15 Views of a Node Link Graph: An Information Visualization Portfolio

Learning Image Patch Representation for Scene Recognition

Learning Object Appearance Models via Transformed Dirichlet Processes

On Conditional Branches in Optimal Decision Trees

Key Phrase Indexing With Controlled Vocabularies

Perceptual Image/Video Segmentation and Semantic Classification

Probabilistic Dimensional Reduction with Gaussian Process Latent Variable Model

Spatial Query Processing Utilizing Voronoi Diagrams

Multiview Geometry for Texture Mapping 2D Images onto 3D Range Data

Extracting Information from Large Graphs by Computing Similarities Between Node

Bay Area Discrete Math Day XII: Method for Linear Programming

Bay Area Discrete Math Day XII: Hierarchial Dirichlet Processes

Bay Area Discrete Math Day XII: Monotonicity in the Ising Model

Bay Area Discrete Math Day XII: The Coloring Torus of a Graph

Bay Area Discrete Math Day XII: Integer Linear Programming

Bay Area Discrete Math Day XII: Stat. Physics, Comp. Simulation, and Probability