Electrical Engineering
      and Computer Sciences

Electrical Engineering and Computer Sciences

COLLEGE OF ENGINEERING

UC Berkeley

Communication Bounds for Heterogeneous Architectures

Grey Ballard, James Demmel and Andrew Gearhart

EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2011-13
February 11, 2011

http://www.eecs.berkeley.edu/Pubs/TechRpts/2011/EECS-2011-13.pdf

As the gap between the cost of communication (i.e., data movement) and computation continues to grow, pursuing algorithms which minimize communication has become a critical research objective. Toward this end, we seek asymptotic communication lower bounds for general memory models and classes of algorithms. Recent work has established lower bounds for a wide set of linear algebra algorithms on a sequential machine and on a parallel machine with identical processors. This work extends these previous bounds to a heterogeneous model in which processors access data and perform floating point operations at differing speeds. We also present algorithms which prove that the lower bounds are tight (i.e., attainable) in the cases of dense matrix-vector and matrix-matrix multiplication.


BibTeX citation:

@techreport{Ballard:EECS-2011-13,
    Author = {Ballard, Grey and Demmel, James and Gearhart, Andrew},
    Title = {Communication Bounds for Heterogeneous Architectures},
    Institution = {EECS Department, University of California, Berkeley},
    Year = {2011},
    Month = {Feb},
    URL = {http://www.eecs.berkeley.edu/Pubs/TechRpts/2011/EECS-2011-13.html},
    Number = {UCB/EECS-2011-13},
    Abstract = {As the gap between the cost of communication (i.e., data movement) and computation continues to grow, pursuing algorithms which minimize communication has become a critical research objective.  Toward this end, we seek asymptotic communication lower bounds for general memory models and classes of algorithms.  Recent work has established lower bounds for a wide set of linear algebra algorithms on a sequential machine and on a parallel machine with identical processors.  This work extends these previous bounds to a heterogeneous model in which processors access data and perform floating point operations at differing speeds.  We also present algorithms which prove that the lower bounds are tight (i.e., attainable) in the cases of dense matrix-vector and matrix-matrix multiplication.}
}

EndNote citation:

%0 Report
%A Ballard, Grey
%A Demmel, James
%A Gearhart, Andrew
%T Communication Bounds for Heterogeneous Architectures
%I EECS Department, University of California, Berkeley
%D 2011
%8 February 11
%@ UCB/EECS-2011-13
%U http://www.eecs.berkeley.edu/Pubs/TechRpts/2011/EECS-2011-13.html
%F Ballard:EECS-2011-13