We address the problem of code-size minimization in VLSI systems with embedded DSP processors. Reducing code size reduces the production cost of embedded systemswe use data-compression methods to develop code-size minimization strategies. In our framework, the compressed program consists of a skeleton and a dictionary. We show that the dictionary can be computed by solving a set-covering problem derived from the original program. To execute the compressed code, we describe two methods that have different performance characteristics and different degrees of freedom in compressing the code. We also address performance considerations, and show that they can be incorporated easily into the set-covering formulation, and present experimental results obtained with Texas Instruments' optimizing TMS3220C25 compiler.
Description
A text-compression-based method for code size minimization in embedded systems
%0 Journal Article
%1 liao99text
%A Liao, Stan
%A Devadas, Srinivas
%A Keutzer, Kurt
%C New York, NY, USA
%D 1999
%I ACM
%J ACM Trans. Des. Autom. Electron. Syst.
%K Code-size Compression Embedded Minimization
%N 1
%P 12--38
%R http://doi.acm.org/10.1145/298865.298867
%T A text-compression-based method for code size minimization in embedded systems
%U http://doi.acm.org/10.1145/298865.298867
%V 4
%X We address the problem of code-size minimization in VLSI systems with embedded DSP processors. Reducing code size reduces the production cost of embedded systemswe use data-compression methods to develop code-size minimization strategies. In our framework, the compressed program consists of a skeleton and a dictionary. We show that the dictionary can be computed by solving a set-covering problem derived from the original program. To execute the compressed code, we describe two methods that have different performance characteristics and different degrees of freedom in compressing the code. We also address performance considerations, and show that they can be incorporated easily into the set-covering formulation, and present experimental results obtained with Texas Instruments' optimizing TMS3220C25 compiler.
@article{liao99text,
abstract = {We address the problem of code-size minimization in VLSI systems with embedded DSP processors. Reducing code size reduces the production cost of embedded systemswe use data-compression methods to develop code-size minimization strategies. In our framework, the compressed program consists of a skeleton and a dictionary. We show that the dictionary can be computed by solving a set-covering problem derived from the original program. To execute the compressed code, we describe two methods that have different performance characteristics and different degrees of freedom in compressing the code. We also address performance considerations, and show that they can be incorporated easily into the set-covering formulation, and present experimental results obtained with Texas Instruments' optimizing TMS3220C25 compiler.},
added-at = {2008-01-20T08:53:04.000+0100},
address = {New York, NY, USA},
author = {Liao, Stan and Devadas, Srinivas and Keutzer, Kurt},
biburl = {https://www.bibsonomy.org/bibtex/2f3a85bd2ad5b850bd75cd0e2fa593c56/derkling},
description = {A text-compression-based method for code size minimization in embedded systems},
doi = {http://doi.acm.org/10.1145/298865.298867},
interhash = {cf5c53e94a1033358275b35e43a1409d},
intrahash = {f3a85bd2ad5b850bd75cd0e2fa593c56},
issn = {1084-4309},
journal = {ACM Trans. Des. Autom. Electron. Syst.},
keywords = {Code-size Compression Embedded Minimization},
number = 1,
pages = {12--38},
publisher = {ACM},
timestamp = {2008-01-20T08:53:04.000+0100},
title = {A text-compression-based method for code size minimization in embedded systems},
url = {http://doi.acm.org/10.1145/298865.298867},
volume = 4,
year = 1999
}