Benjamin Puitong Lam

• MComp (Hons) Computing Science (Study Abroad)
• Genetic DSE: Implementing and evaluating advanced algorithms for automated exploration of design spaces for cyber-physical systems

Cyber-Physical Systems (CPSs) combine computing processes with physical processes, human and other elements to deliver a global behaviour. They exist all around us- from pacemakers to power grids! Designing CPSs is challenging because we need to need to make compromises between factors such as performance, energy consumption and/or security. Finding the best CPS designs involves exploring vast numbers of alternatives to find optimal trade-offs. This is called Design Space Exploration (DSE).

This project implements genetic algorithms for DSE and investigates whether they can find better designs more efficiently than evaluating every possible design. Genetic algorithms are processes which try to find better designs by drawing inspiration from evolutionary processes in nature by “breeding” new generations of improved designs from the best of the previous generation. This could be significant because they could save the engineer time and effort in creating designs that reduce emissions, energy and/or raw material costs.

Funding source: Newcastle University

Supervisor: Prof John S Fitzgerald