TY - JOUR
T1 - Evolving Behavioural Level Sequence Detectors in SystemVerilog Using Grammatical Evolution
AU - Majeed, Bilal
AU - Ryan, Conor
AU - McEllin, Jack
AU - Youssef, Ayman
AU - Mota Dias, Douglas
AU - Murphy, Aidan
AU - Carvalho, Samuel
N1 - Publisher Copyright:
© 2023 by SCITEPRESS – Science and Technology Publications, Lda.
PY - 2023
Y1 - 2023
N2 - Sequential circuits are time-dependent circuits whose output depends not only on their current inputs but also on previous ones. This makes them substantially more complex than combinational circuits, which are stateless and only produce outputs from their current inputs. This paper demonstrates the automatic evolution of some of the most critical and hard-to-evolve electronic sequential circuits, namely, sequence detectors. The circuits are generated at behavioural level using the Hardware Description Language, SystemVerilog. We successfully evolve solutions ranging in complexity from 3 to 5 bits, with and without encapsulation, and 6 bits with encapsulation while using Grammatical Evolution. A uniform distribution of values that a vector of 50 bits can represent was used to generate the random training and test data sets to prevent any bias in the solutions and results. While previous work combined shorter sequence detectors to produce longer ones, for example, combining two 3-bit detectors to form a 6-bit detector, we produce all sequence detectors from scratch without any intermediate stages. The system simply takes instructions and testcases and produces the desired detector; we show that not only does it produce longer-sequence detectors than previous work, but it also does it using fewer computational resources.
AB - Sequential circuits are time-dependent circuits whose output depends not only on their current inputs but also on previous ones. This makes them substantially more complex than combinational circuits, which are stateless and only produce outputs from their current inputs. This paper demonstrates the automatic evolution of some of the most critical and hard-to-evolve electronic sequential circuits, namely, sequence detectors. The circuits are generated at behavioural level using the Hardware Description Language, SystemVerilog. We successfully evolve solutions ranging in complexity from 3 to 5 bits, with and without encapsulation, and 6 bits with encapsulation while using Grammatical Evolution. A uniform distribution of values that a vector of 50 bits can represent was used to generate the random training and test data sets to prevent any bias in the solutions and results. While previous work combined shorter sequence detectors to produce longer ones, for example, combining two 3-bit detectors to form a 6-bit detector, we produce all sequence detectors from scratch without any intermediate stages. The system simply takes instructions and testcases and produces the desired detector; we show that not only does it produce longer-sequence detectors than previous work, but it also does it using fewer computational resources.
KW - Electronic Design Automation
KW - Evolvable Hardware
KW - Grammatical Evolution
KW - Hardware Description Language Design
KW - Sequence Detectors
KW - Sequential Logic Circuits
UR - http://www.scopus.com/inward/record.url?scp=85177210105&partnerID=8YFLogxK
U2 - 10.5220/0011689100003393
DO - 10.5220/0011689100003393
M3 - Conference article
AN - SCOPUS:85177210105
SN - 2184-3589
VL - 3
SP - 475
EP - 483
JO - International Conference on Agents and Artificial Intelligence
JF - International Conference on Agents and Artificial Intelligence
T2 - 15th International Conference on Agents and Artificial Intelligence, ICAART 2023
Y2 - 22 February 2023 through 24 February 2023
ER -