SCHEDULE: NOV 10-16, 2012
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Automatically Adapting Programs for Mixed-Precision Floating-Point Computation
SESSION: Research Poster Reception
EVENT TYPE: Posters and Electronic Posters
TIME: 5:15PM - 7:00PM
SESSION CHAIR: Torsten Hoefler
AUTHOR(S):Michael O. Lam, Bronis R. de Supinski, Matthew P. LeGendre, Jeffrey K. Hollingsworth
ROOM:East Entrance
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.
Chair/Author Details:
Torsten Hoefler (Chair) - ETH Zurich
Michael O. Lam - University of Maryland
Bronis R. de Supinski - Lawrence Livermore National Laboratory
Matthew P. LeGendre - Lawrence Livermore National Laboratory
Jeffrey K. Hollingsworth - University of Maryland
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Automatically Adapting Programs for Mixed-Precision Floating-Point Computation
SESSION: Research Poster Reception
EVENT TYPE:
TIME: 5:15PM - 7:00PM
SESSION CHAIR: Torsten Hoefler
AUTHOR(S):Michael O. Lam, Bronis R. de Supinski, Matthew P. LeGendre, Jeffrey K. Hollingsworth
ROOM:East Entrance
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.
Chair/Author Details:
Torsten Hoefler (Chair) - ETH Zurich
Michael O. Lam - University of Maryland
Bronis R. de Supinski - Lawrence Livermore National Laboratory
Matthew P. LeGendre - Lawrence Livermore National Laboratory
Jeffrey K. Hollingsworth - University of Maryland
Click here to download .ics calendar file