[Amath-seminars] James Demmel -- Boeing Colloquium (January 25, 4pm)
N. Benjamin Erichson
erichson at uw.edu
Wed Jan 17 15:35:54 PST 2018
We are pleased to invite you to the Applied Math Department's Boeing Distinguished Colloquium delivered by Prof. James Demmel from the University of California at Berkeley.
Prof. Demmel is the Dr. Richard Carl Dehmel Distinguished Professor of Computer Science and Mathematics at the University of California at Berkeley, and Chair of the EECS Dept. His research is in numerical linear algebra, HPC, and communication avoiding algorithms. He is known for his work on the LAPACK and ScaLAPACK linear algebra libraries. He is a member of the NAS, NAE, a Fellow of the AAAS, ACM, AMS, IEEE and SIAM, and winner of the IPDPS Charles Babbage Award, IEEE Computer Society Sidney Fernbach Award, the ACM Paris Kanellakis Award, and numerous best paper prizes.
James Demmel, Boeing Distinguished Colloquium
When: Thursday, January 25 at 4 PM
Where: Smith Hall 205
The talk will be followed by a reception in the Lewis hall lounge.
The title and abstract are given below:
Communication-Avoiding Algorithms for Linear Algebra and Beyond
Algorithms have two costs: arithmetic and communication, i.e. moving data between levels of a memory hierarchy or processors over a network. Communication costs (measured in time or energy per operation) already greatly exceed arithmetic costs, and the gap is growing over time following technological trends. Thus our goal is to design algorithms that minimize communication. We present algorithms that attain provable lower bounds on communication, and show large speedups compared to their conventional counterparts. These algorithms include direct and iterative linear algebra, for dense and sparse matrices, direct n-body simulations, and some machine learning algorithms. Several of these algorithms exhibit perfect strong scaling, in both time and energy: run time (resp. energy) for a fixed problem size drops proportionally to the number of processors p (resp. is independent of p). Finally, using recent extensions of the Holder-Brascamp-Lieb inequalities, we show how to generalize our approach to algorithms involving arbitrary loop nests and array accesses, assuming only that array subscripts are affine functions of the loop indices.
Gabrielle & Ben
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