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@inproceedings{jha-nsv13,
author = {Susmit Jha and Sanjit A. Seshia},
title = {Synthesis of Optimal Fixed-Point Implementations of Numerical Software Routines},
booktitle = {Proc. Sixth International Workshop on Numerical Software Verification (NSV)},
month = "April",
year = {2013},
abstract = {In this paper, we present an automated technique SWATI: Synthesizing
Wordlengths Automatically Using Testing and Induction, which uses a combination
of Nelder-Mead optimization based testing, and induction from examples
to automatically synthesize optimal fixedpoint implementation of numerical routines.
The design of numerical software is commonly done using floating-point
arithmetic in design-environments such as Matlab. However, these designs are
often implemented using fixed-point arithmetic for speed and efficiency reasons
especially in embedded systems. The fixed-point implementation reduces implementation
cost, provides better performance, and reduces power consumption.
The conversion from floating-point designs to fixed-point code is subject to two
opposing constraints: (i) the word-width of fixed-point types must be minimized,
and (ii) the outputs of the fixed-point program must be accurate. In this paper,
we propose a new solution to this problem. Our technique takes the floating-point
program, specified accuracy and an implementation cost model and provides the
fixed-point program with specified accuracy and optimal implementation cost.
We demonstrate the effectiveness of our approach on a set of examples from the
domain of automated control, robotics and digital signal processing.},
}