Name
Abstract | ||
|---|---|---|
1 Decomposition is an effective way to reduce power in finite-state machines (FSMs) synthesis. In this study, we proposed a fuzzy c-mean clustering based decomposition method, called FCM-D, for FSM synthesis. FCM-D partitions a set of states of FSM into a collection of c fuzzy clusters; hence a FSM is decomposed into several sub machines. The objective function is to minimize the cross state transition probability between sub machines and increase the inner state transition probability within each sub machine. We test our approach on seven benchmarks, and the experimental results show FCM-D achieved a significant reduction on dynamic power and leakage power consumption. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/3067695.3075988 | GECCO (Companion) |
Keywords | Field | DocType |
Finite state machine, power consumptions reduction, dynamic power, leakage power, decomposition, fuzzy c-mean clustering | Mathematical optimization,Fuzzy clusters,Computer science,Fuzzy logic,Leakage power,Finite-state machine,Decomposition method (constraint satisfaction),Dynamic demand,Cluster analysis,Decomposition | Conference |
ISBN | Citations | PageRank |
978-1-4503-4939-0 | 0 | 0.34 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yanyun Tao | 1 | 0 | 1.69 |
| Yuzhen Zhang | 2 | 14 | 3.99 |
| Qinyu Wang | 3 | 0 | 1.01 |