Doing Moore with Less -- Leapfrogging Moore's Law with Inexactness for Supercomputing
Abstract
Energy and power consumption are major limitations to continued scaling of computing systems. Inexactness, where the quality of the solution can be traded for energy savings, has been proposed as an approach to overcoming those limitations. In the past, however, inexactness necessitated the need for highly customized or specialized hardware. The current evolution of commercial off-the-shelf(COTS) processors facilitates the use of lower-precision arithmetic in ways that reduce energy consumption. We study these new opportunities in this paper, using the example of an inexact Newton algorithm for solving nonlinear equations. Moreover, we have begun developing a set of techniques we call reinvestment that, paradoxically, use reduced precision to improve the quality of the computed result: They do so by reinvesting the energy saved by reduced precision.
Cite
@article{arxiv.1610.02606,
title = {Doing Moore with Less -- Leapfrogging Moore's Law with Inexactness for Supercomputing},
author = {Sven Leyffer and Stefan M. Wild and Mike Fagan and Marc Snir and Krishna Palem and Kazutomo Yoshii and Hal Finkel},
journal= {arXiv preprint arXiv:1610.02606},
year = {2016}
}
Comments
9 pages, 12 figures, PDFLaTeX. 12 Oct 2016: Corrected author Hal Finkel's affiliation to show ALCF/Argonne