National Repository of Grey Literature 4 records found  Search took 0.01 seconds. 
Evolutionary Design for Circuit Approximation
Dvořáček, Petr ; Vašíček, Zdeněk (referee) ; Sekanina, Lukáš (advisor)
In recent years, there has been a strong need for the design of integrated  circuits showing low power consumption. It is possible to create intentionally approximate circuits which don't fully implement the specified logic behaviour, but exhibit improvements in term of area, delay and power consumption. These circuits can be used in many error resilient applications, especially in signal and image processing, computer graphics, computer vision and machine learning. This work describes an evolutionary approach to approximate design of arithmetic circuits and other more complex systems. This text presents a parallel calculation of a fitness function. The proposed method accelerated evaluation of 8-bit approximate multiplier 170 times in comparison with the common version. Evolved approximate circuits were used in different types of edge detectors.
Employing Approximate Equivalence for Design of Approximate Circuits
Matyáš, Jiří ; Lengál, Ondřej (referee) ; Češka, Milan (advisor)
This thesis is concerned with the utilization of formal verification techniques in the design of the functional approximations of combinational circuits. We thoroughly study the existing formal approaches for the approximate equivalence checking and their utilization in the approximate circuit development. We present a new method that integrates the formal techniques into the Cartesian Genetic Programming. The key idea of our approach is to employ a new search strategy that drives the evolution towards promptly verifiable candidate solutions. The proposed method was implemented within ABC synthesis tool. Various parameters of the search strategy were examined and the algorithm's performance was evaluated on the functional approximations of multipliers and adders with operand widths up to 32 and 128 bits respectively. Achieved results show an unprecedented scalability of our approach.
Employing Approximate Equivalence for Design of Approximate Circuits
Matyáš, Jiří ; Lengál, Ondřej (referee) ; Češka, Milan (advisor)
This thesis is concerned with the utilization of formal verification techniques in the design of the functional approximations of combinational circuits. We thoroughly study the existing formal approaches for the approximate equivalence checking and their utilization in the approximate circuit development. We present a new method that integrates the formal techniques into the Cartesian Genetic Programming. The key idea of our approach is to employ a new search strategy that drives the evolution towards promptly verifiable candidate solutions. The proposed method was implemented within ABC synthesis tool. Various parameters of the search strategy were examined and the algorithm's performance was evaluated on the functional approximations of multipliers and adders with operand widths up to 32 and 128 bits respectively. Achieved results show an unprecedented scalability of our approach.
Evolutionary Design for Circuit Approximation
Dvořáček, Petr ; Vašíček, Zdeněk (referee) ; Sekanina, Lukáš (advisor)
In recent years, there has been a strong need for the design of integrated  circuits showing low power consumption. It is possible to create intentionally approximate circuits which don't fully implement the specified logic behaviour, but exhibit improvements in term of area, delay and power consumption. These circuits can be used in many error resilient applications, especially in signal and image processing, computer graphics, computer vision and machine learning. This work describes an evolutionary approach to approximate design of arithmetic circuits and other more complex systems. This text presents a parallel calculation of a fitness function. The proposed method accelerated evaluation of 8-bit approximate multiplier 170 times in comparison with the common version. Evolved approximate circuits were used in different types of edge detectors.

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