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| Project number |
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Erwin Schrödinger Fellowships
J2322
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| Title |
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Advanced Code Generation in Digital Signal Processing |
| Principal investigator |
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FRANCHETTI Franz |
| Approval date |
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24.06.2003 |
| University / Research institution |
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Department of Electrical and Computer Engineering, Carnegie Mellon University |
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Institut für Angewandte und Numerische Mathematik, Technische Universität Wien |
| Scientific field(s) |
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| Keywords |
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Code Generation, Digital signal Processing, Short Vector SIMD Extensions, Automatic Performance Tuning, Discrete Linear Transforms |
| Homepage |
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http://www.ece.cmu.edu/~franzf
|
Numerical software of the future will be different from what it looks nowadays.
Nevertheless, reliability, portability across the rapidly evolving platforms,
and satisfactory run time efficiency will remain to be standard requirements requested
from high quality software. However, continually increasing problem sizes, computing
environments which are exceedingly difficult to utilize, and new ways of software
usage via the Internet and computational grids make it harder and harder to achieve
these traditional goals. Special purpose numerical software in conjunction with
special purpose compilers will gain in importance. This evolution of a radically
new way of software development will be pursued in the proposed research project.
The ultimate goal is to automate the process of architecture dependent performance
tuning. The proposed two-year research project will deal with the machine
generation of high-performance implementations of discrete linear transform algorithms
that are automatically adapted to a given computing platform. Code generated by
applying the newly developed methods will take full advantage of modern architectural
features and instruction set extensions, deep memory hierarchies, software initiated
prefetching, as well as multiple CPUs in both shared memory and distributed memory
multiprocessors, up to IBM's top performance computers of BG/L type. Research
will concentrate on discrete linear transforms like Fourier transforms, sine and
cosine transforms, as well as wavelet transforms.
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Disclaimer |
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The content is not edited by the FWF, and the sole responsibility therefore lies with the author. |
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