Lecture 1: Implications of the exascale roadmap for algorithms

Sunday, January 9, 2011 - 9:30am - 10:30am
Lind 305
David Keyes (Columbia University)
The central challenge in progressing from petascale to exascale
supercomputing is the same as that in progressing from gigascale to
terascale personal computing: strong scaling within shared memory on a
single node of up to 1K simultaneously active computational threads.
Many issues in algorithmic design and implementation are identical in
these two simultaneous quests; however, the exascale quest has
additional challenges due to practical limits on total power
consumption (which come at the expense of resilience and node
performance uniformity), to system-scale reliability (due to more
points of failure), and to the need to merge the on-node programming
environment with a million others (a weak scaling that is not in
itself difficult, but will lead to challenges of coordination). This
lecture series presents the issues, as digested from recent US
Department of Energy roadmapping exercises, and focuses attention on
some new issues that require mathematical attention. It is intended
to provide those new to exascale computing with a working background
for the week ahead, and motivation for the GPU scientific programming
unit of the tutorial.
MSC Code: