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[http://www.icsi.berkeley.edu/~dbailey/ David H Bailey], Lawrence Berkeley Lab [http://crd.lbl.gov/~dhbailey/ David H Bailey], Lawrence Berkeley Lab

These are the abstracts for all the talks scheduled for the workshop, listed in alphabetical order. For times, see the [:msri07/schedule: schedule] itself.


Bailey: Experimental Mathematics and High-Performance Computing

[http://crd.lbl.gov/~dhbailey/ David H Bailey], Lawrence Berkeley Lab


Recent developments in "experimental mathematics" have underscored the value of high-performance computing in modern mathematical research. The most frequent computations that arise here are high-precision (typically several-hundred-digit accuracy) evaluations of integrals and series, together with integer relation detections using the "PSLQ" algorithm. Some recent highlights in this arena include: (2) the discovery of "BBP"-type formulas for various mathematical constants, including pi and log(2); (3) the discovery of analytic evaluations for several classes of multivariate zeta sums; (4) the discovery of Apery-like formulas for the Riemann zeta function at integer arguments; and (5) the discovery of analytic evaluations and linear relations among certain classes of definite integrals that arise in mathematical physics. The talk will include a live demo of the "experimental mathematician's toolkit".

Cohn: <TITLE>

[http://research.microsoft.com/~cohn/ Henry Cohn (Microsoft Research)]

Cooperman: <TITLE>

[http://www.ccs.neu.edu/home/gene/ Gene Cooperman (Northeastern University)]

Edelman: <TITLE>

[http://www-math.mit.edu/~edelman/ Alan Edelman (MIT)]

Granger: Interactive Parallel Computing using Python and IPython

[http://txcorp.com Brian Granger - Tech X Corp.]

Interactive computing environments, such as Matlab, IDL and Mathematica are popular among researchers because their interactive nature is well matched to the exploratory nature of research. However, these systems have one critical weakness: they are not designed to take advantage of parallel computing hardware such as multi-core CPUs, clusters and supercomputers. Thus, researchers usually turn to non-interactive compiled languages, such as C/C++/Fortran when parallelism is needed.

In this talk I will describe recent work on the IPython project to implement a software architecture that allows parallel applications to be developed, debugged, tested, executed and monitored in a fully interactive manner using the Python programming language. This system is fully functional and allows many types of parallelism to be expressed, including message passing (using MPI), task farming, shared memory, and custom user defined approaches. I will describe the architecture, provide an overview of its basic usage and then provide more sophisticated examples of how it can be used in the development of new parallel algorithms. Because IPython is one of the components of the SAGE system, I will also discuss how IPython's parallel computing capabilities can be used in that context.

Harrison: Science at the petascale --- tools in the tool box.

[http://www.csm.ornl.gov/ccsg/html/staff/harrison.html Robert Harrison ] (Oak Ridge National Lab)

Petascale computing will require coordinating the actions of 100,000+ processors, and directing the flow of data between up to six levels of memory hierarchy and along channels that differ by over a factor of 100 in bandwidth. Amdahl's law requires that petascale applications have less than 0.001% sequential or replicated work in order to be at least 50% efficient. These are profound challenges for all but the most regular or embarrassingly parallel applications, yet we also demand that not just bigger and better, but fundamentally new science. In this presentation I will discuss how we are attempting to confront simultaneously the complexities of petascale computation while increasing our scientific productivity. I hope that I can convince you that our development of MADNESS (multiresolution adaptive numerical scientific simulation) is not as crazy as it sounds.

This work is funded by the U.S. Department of Energy, the division of Basic Energy Science, Office of Science, and was performed in part using resources of the National Center for Computational Sciences, both under contract DE-AC05-00OR22725 with Oak Ridge National Laboratory.

Hart: <TITLE>

[http://www.maths.warwick.ac.uk/~masfaw/ Bill Hart (Warwick)]

Hida: <TITLE>

[http://www.cs.berkeley.edu/~yozo/ Yozo Hida (UC Berkeley)]

Martin: <TITLE>

[http://www.math.jmu.edu/~martin/ Jason Martin (James Madison University)]

Maza-Xie: <TITLE>

[http://www.csd.uwo.ca/~moreno/ Moreno Maza and Xie (Western Ontario)]

Noel: <TITLE>

[http://www.math.umb.edu/~anoel/ Alfred Noel (UMass Boston / MIT)]

Qiang: <TITLE>

[http://www.yiqiang.net/ Yi Qiang (UW)]

Roch: <TITLE>

[http://www-id.imag.fr/Laboratoire/Membres/Roch_Jean-Louis/perso.html Jean-Louis Roch (France)]

Verschelde: <TITLE>

[http://www.math.uic.edu/~jan/ Jan Verschelde (UIC)]

Yelick: <TITLE>

[http://www.cs.berkeley.edu/~yelick/ Kathy Yelick (UC Berkeley)]

msri07/abstracts (last edited 2008-11-14 13:41:59 by anonymous)