Abstract
This paper presents parallel algorithms for fuzzy arithmetic operations on systolic arrays. A large part of the arithmetic on fuzzy numbers is referred to as fuzzy convolutions, which take O(n2) time steps when implemented sequentially. In this paper, we present two parallel algorithms. The first algorithm runs on a linear array machine in O(n) time, using O(n) processors, and thus, achieving optimal time and cost. The second algorithm runs on a mesh-of-trees type of computer architecture in L(log n) time steps, using O(n2) processors. The latter, although not optimal achieved high speedup. Both can be adapted to handle larger linear fuzzy numbers of fuzzy numbers with higher dimension.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1283-1301 |
| Number of pages | 19 |
| Journal | Parallel Computing |
| Volume | 19 |
| Issue number | 11 |
| DOIs | |
| State | Published - Jan 1 1993 |
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Keywords
- fuzzy arithmetic
- linear array of processors
- mesh-of-trees of processors
- speed-up analysis
- Systolic arrays
ASJC Scopus subject areas
- Theoretical Computer Science
- Software
- Hardware and Architecture
- Computer Networks and Communications
- Computer Graphics and Computer-Aided Design
- Artificial Intelligence
Cite this
Fuzzy arithmetic on systolic arrays. / Dhrif, Hassen; Sarkar, Dilip.
In: Parallel Computing, Vol. 19, No. 11, 01.01.1993, p. 1283-1301.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Fuzzy arithmetic on systolic arrays
AU - Dhrif, Hassen
AU - Sarkar, Dilip
PY - 1993/1/1
Y1 - 1993/1/1
N2 - This paper presents parallel algorithms for fuzzy arithmetic operations on systolic arrays. A large part of the arithmetic on fuzzy numbers is referred to as fuzzy convolutions, which take O(n2) time steps when implemented sequentially. In this paper, we present two parallel algorithms. The first algorithm runs on a linear array machine in O(n) time, using O(n) processors, and thus, achieving optimal time and cost. The second algorithm runs on a mesh-of-trees type of computer architecture in L(log n) time steps, using O(n2) processors. The latter, although not optimal achieved high speedup. Both can be adapted to handle larger linear fuzzy numbers of fuzzy numbers with higher dimension.
AB - This paper presents parallel algorithms for fuzzy arithmetic operations on systolic arrays. A large part of the arithmetic on fuzzy numbers is referred to as fuzzy convolutions, which take O(n2) time steps when implemented sequentially. In this paper, we present two parallel algorithms. The first algorithm runs on a linear array machine in O(n) time, using O(n) processors, and thus, achieving optimal time and cost. The second algorithm runs on a mesh-of-trees type of computer architecture in L(log n) time steps, using O(n2) processors. The latter, although not optimal achieved high speedup. Both can be adapted to handle larger linear fuzzy numbers of fuzzy numbers with higher dimension.
KW - fuzzy arithmetic
KW - linear array of processors
KW - mesh-of-trees of processors
KW - speed-up analysis
KW - Systolic arrays
UR - http://www.scopus.com/inward/record.url?scp=0027694926&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0027694926&partnerID=8YFLogxK
U2 - 10.1016/0167-8191(93)90032-G
DO - 10.1016/0167-8191(93)90032-G
M3 - Article
AN - SCOPUS:0027694926
VL - 19
SP - 1283
EP - 1301
JO - Parallel Computing
JF - Parallel Computing
SN - 0167-8191
IS - 11
ER -