IEICE TRANSACTIONS on Fundamentals
A Hierarchical Clustering Method for the Multiple Constant Multiplication Problem
Summary :
In this paper, we propose an efficient solution for the Multiple Constant Multiplication (MCM) problem. The method uses hierarchical clustering to exploit common subexpressions among constants and reduces the number of shifts, additions, and subtractions. The algorithm defines appropriate weights, which indicate operation priority, and selects common subexpressions, resulting in a minimum number of local operations. It can also be extended to various high-level synthesis tasks such as arbitrary linear transforms. Experimental results for several error-correcting codes, digital filters and Discrete Cosine Transforms (DCTs) have shown the effectiveness of our method.
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- IEICE TRANSACTIONS on Fundamentals Vol.E80-A No.10 pp.1767-1773
- Publication Date
- 1997/10/25
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- Special Section PAPER (Special Section on VLSI Design and CAD Algorithms)
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Akihiro MATSUURA, Mitsuteru YUKISHITA, Akira NAGOYA, "A Hierarchical Clustering Method for the Multiple Constant Multiplication Problem" in IEICE TRANSACTIONS on Fundamentals,
vol. E80-A, no. 10, pp. 1767-1773, October 1997, doi: .
Abstract: In this paper, we propose an efficient solution for the Multiple Constant Multiplication (MCM) problem. The method uses hierarchical clustering to exploit common subexpressions among constants and reduces the number of shifts, additions, and subtractions. The algorithm defines appropriate weights, which indicate operation priority, and selects common subexpressions, resulting in a minimum number of local operations. It can also be extended to various high-level synthesis tasks such as arbitrary linear transforms. Experimental results for several error-correcting codes, digital filters and Discrete Cosine Transforms (DCTs) have shown the effectiveness of our method.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e80-a_10_1767/_p
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@ARTICLE{e80-a_10_1767,
author={Akihiro MATSUURA, Mitsuteru YUKISHITA, Akira NAGOYA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Hierarchical Clustering Method for the Multiple Constant Multiplication Problem},
year={1997},
volume={E80-A},
number={10},
pages={1767-1773},
abstract={In this paper, we propose an efficient solution for the Multiple Constant Multiplication (MCM) problem. The method uses hierarchical clustering to exploit common subexpressions among constants and reduces the number of shifts, additions, and subtractions. The algorithm defines appropriate weights, which indicate operation priority, and selects common subexpressions, resulting in a minimum number of local operations. It can also be extended to various high-level synthesis tasks such as arbitrary linear transforms. Experimental results for several error-correcting codes, digital filters and Discrete Cosine Transforms (DCTs) have shown the effectiveness of our method.},
keywords={},
doi={},
ISSN={},
month={October},}
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TY - JOUR
TI - A Hierarchical Clustering Method for the Multiple Constant Multiplication Problem
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1767
EP - 1773
AU - Akihiro MATSUURA
AU - Mitsuteru YUKISHITA
AU - Akira NAGOYA
PY - 1997
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E80-A
IS - 10
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - October 1997
AB - In this paper, we propose an efficient solution for the Multiple Constant Multiplication (MCM) problem. The method uses hierarchical clustering to exploit common subexpressions among constants and reduces the number of shifts, additions, and subtractions. The algorithm defines appropriate weights, which indicate operation priority, and selects common subexpressions, resulting in a minimum number of local operations. It can also be extended to various high-level synthesis tasks such as arbitrary linear transforms. Experimental results for several error-correcting codes, digital filters and Discrete Cosine Transforms (DCTs) have shown the effectiveness of our method.
ER -
English
