[BANANA] LAPACK seminar on Oct. 21

[Ming Gu]

               Math 290, Section 25, CS 298, Section 6,
                          FALL 2009
         (Matrix Computations and Scientific Computing)

We meet WEDNESDAYS 11:10 - noon in Room 380 Soda Hall, Berkeley campus.
The coordinators are Profs. J. Demmel (demmel at cs.berkeley.edu), 
M. Gu (mgu at math.berkeley.edu), and B. N. Parlett (parlett at math.berkeley.edu). 
The program will be a mixture of research talks and tutorials.
The tutorials will provide a partial sequel to Math 221.

For more details about the seminar, please visit
math.berkeley.edu/~mgu/LAPACKSeminar.htm

Date: Oct. 21
Speaker: Prof. Jim Demmel, UC Berkeley
Title:  Minimizing Communication in Linear Algebra
Abstract: Algorithms have two kinds of costs: arithmetic and
communication, by which we mean moving data either between
levels of a memory hierarchy (in the sequential case) or
between processors over a network (in the parallel
case). Communication costs can already exceed arithmetic
costs by orders of magnitude, and the gap is growing
exponentially over time, so our goal is to design linear
algebra algorithms that minimize communication. First, we
show how to extend known communication lower bounds for
O(n^3) dense matrix multiplication to all direct linear
algebra, i.e.  for solving linear systems, least squares
problems, eigenproblems and the SVD, for dense or sparse
matrices, and for sequential or parallel machines. We also
describe dense algorithms that attain these lower bounds;
some implementations attain large speed ups over
conventional algorithms. Second, we show how to minimize
communication in Krylov-subspace methods for solving sparse
linear system and eigenproblems, and again demonstrate new
algorithms with significant speedups.