Paper Info
Title
Abstract: Automatically Adapting Programs for Mixed-Precision Floating-Point Computation
Abstract
As scientific computation continues to scale, it is crucial to use floating-point arithmetic processors as efficiently as possible. Lower precision allows streaming architectures to perform more operations per second and can reduce memory bandwidth pressure on all architectures. However, using a precision that is too low for a given algorithm and data set will result in inaccurate results. In this poster, we present a framework that uses binary instrumentation and modification to build mixed-precision configurations of existing binaries that were originally developed to use only double-precision. This allows developers to easily experiment with mixed-precision configurations without modifying their source code, and it permits auto-tuning of floating-point precision. We also implemented a simple search algorithm to automatically identify which code regions can use lower precision. We include results for several benchmarks that show both the efficacy and overhead of our tool.
Year
DOI
Venue
2012
10.1109/SC.Companion.2012.231
SC Companion
Keywords
DocType
Citations 
floating point arithmetic,algebra
Conference
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Michael O. Lam1505.15
de Supinski, Bronis R.22667154.44
Matthew LeGendre3685.67
Jeffrey K. Hollingsworth41881192.59