SCHEDULE: NOV 16-22, 2013
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Automated Floating-point Program Analysis
SESSION: Doctoral Showcase - Dissertation Research
EVENT TYPE: Doctoral Showcase - Dissertation Research Showcase
TIME: 1:45PM - 2:00PM
SESSION CHAIR: Alistair Rendell
Presenter(s):Michael O. Lam
ROOM:601/603
ABSTRACT:
As scientific computation continues to scale, it is crucial to use floating-point arithmetic as efficiently as possible. Lower precision allows streaming architectures to perform more operations per second and can reduce memory bandwidth pressure. However, using a precision that is too low will result in inaccurate results. Thus, developers must balance speed and accuracy when choosing the floating-point precision of their subroutines and data structures.
I have developed program analysis techniques to help developers learn about the runtime floating-point behavior of their programs, with the goal of helping them make decisions concerning the choice of precision in implementation. I have developed automated methods for cancellation detection, range tracking, mixed-precision configuration, mixed-precision search, and bit-level sensitivity analysis. This body of work improves the state of the field of program analysis and scientific computing by providing insights that were not previously available using automated analysis techniques.
Chair/Presenter Details:
Alistair Rendell (Chair) - Australian National University
Michael O. Lam - University of Maryland, College Park
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