Area and Performance Estimates of Finite State Machines in Reconfigurable Systems DOI Creative Commons
Valery Salauyou

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(24), P. 11833 - 11833

Published: Dec. 18, 2024

Modern reconfigurable systems are typically implemented in field-programmable gate arrays (FPGAs) based on look-up tables (LUTs). Finite state machines (FSMs) perform the functions of control devices and integral to systems. When designing systems, problem optimizing area performance FSMs often arises. The FSM synthesis encoding methods generally use only one estimate or performance. However, regardless computational complexity method, if incorrectly reflects optimization aim, result is far from optimal solution. This paper proposes several estimates LUT-based FPGAs. effectiveness proposed was investigated using sequential method for encoding. Experimental studies benchmarks showed that decreases average 3.8% 6.5%, compared known approaches (for some cases by 33.3%), while increases 3.5% 7.3% 27.6%). Recommendations practical also provided. Conclusions section highlights promising directions future research.

Language: Английский

Area and Performance Estimates of Finite State Machines in Reconfigurable Systems DOI Creative Commons
Valery Salauyou

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(24), P. 11833 - 11833

Published: Dec. 18, 2024

Modern reconfigurable systems are typically implemented in field-programmable gate arrays (FPGAs) based on look-up tables (LUTs). Finite state machines (FSMs) perform the functions of control devices and integral to systems. When designing systems, problem optimizing area performance FSMs often arises. The FSM synthesis encoding methods generally use only one estimate or performance. However, regardless computational complexity method, if incorrectly reflects optimization aim, result is far from optimal solution. This paper proposes several estimates LUT-based FPGAs. effectiveness proposed was investigated using sequential method for encoding. Experimental studies benchmarks showed that decreases average 3.8% 6.5%, compared known approaches (for some cases by 33.3%), while increases 3.5% 7.3% 27.6%). Recommendations practical also provided. Conclusions section highlights promising directions future research.

Language: Английский

Citations

2