Paul Richmond -Tutorial -Large Scale Agent Based Modelling w/ FLAME GPU 2
Tutorial - Large Scale Agent Based Modelling with FLAME GPU 2 - FLAME GPU 2 Keywords: Agent Based Modelling and Simulation, GPUs, large scale simulation Organizers: Paul Richmond Modelling and simulation of complex problems has become an established ‘third pillar’ of science, complementary to theory and experimentation. The multi-agent approach to modelling allows complex systems to be constructed in such a way as to add complexity from understanding at an individual level (i.e. a bottom-up approach). This approach is extremely powerful in a wide range of domains as diverse as computational biology to economics and physics. Whilst multi-agent modelling provides a natural and intuitive method to model systems the computational cost of performing large simulations is much greater than for top-down, system level alternatives. In order for multi-agent modelling and simulation to be used as a tool for delivering excellent science, it is vital that simulation performance can scale by targeting readily available computational resources effectively. In other words, increasing the size of the model or its accuracy directly impacts the amount of computational time required to perform the simulation. The use of parallel resources allows us to reduce time constraints and thus scale up the size and increase the accuracy of the model . FLAME GPU 2 provides this computational capacity by targeting readily available Graphics Processing Units capable of simulating many millions of interacting agents with performance which exceeds that of traditional CPU based simulators. FLAME GPU 2 is the next generation of the FLAME GPU software, developed in the UK since 2008 and delivered as a tutorial at ALIFE in 2018 and 2019. FLAME GPU 2 is an agent-based modelling simulation platform that enables modellers from various disciplines like economics, biology and social sciences to easily write agent-based models. Importantly, it abstracts the complexities of the GPU architecture away from modellers to ensure that modellers can concentrate on writing models without the need to acquire specialist knowledge typically required to utilise GPU architectures. This tutorial is aimed at the intermediate level. No knowledge of GPUs is required however basic knowledge multi agent modelling approaches is expected (i.e. formulating a problem as a set of individuals within a system) as well as a basic programming ability. The tutorial format is an introductory lecture followed by participants being provided the opportunity to complete a hands on exercise using the FLAME GPU software. Participants will be provided dedicated GPU cloud resources for interactively configuring and running a large scale agent based model within FLAME GPU. By the end of the practical session, it is expected that the participants will understand how to write and execute a multi-agent model for FLAME GPU from scratch. Participants will leave with an appreciation of the key techniques, concepts, and algorithms which have been used.
Tutorial - Large Scale Agent Based Modelling with FLAME GPU 2 - FLAME GPU 2 Keywords: Agent Based Modelling and Simulation, GPUs, large scale simulation Organizers: Paul Richmond Modelling and simulation of complex problems has become an established ‘third pillar’ of science, complementary to theory and experimentation. The multi-agent approach to modelling allows complex systems to be constructed in such a way as to add complexity from understanding at an individual level (i.e. a bottom-up approach). This approach is extremely powerful in a wide range of domains as diverse as computational biology to economics and physics. Whilst multi-agent modelling provides a natural and intuitive method to model systems the computational cost of performing large simulations is much greater than for top-down, system level alternatives. In order for multi-agent modelling and simulation to be used as a tool for delivering excellent science, it is vital that simulation performance can scale by targeting readily available computational resources effectively. In other words, increasing the size of the model or its accuracy directly impacts the amount of computational time required to perform the simulation. The use of parallel resources allows us to reduce time constraints and thus scale up the size and increase the accuracy of the model . FLAME GPU 2 provides this computational capacity by targeting readily available Graphics Processing Units capable of simulating many millions of interacting agents with performance which exceeds that of traditional CPU based simulators. FLAME GPU 2 is the next generation of the FLAME GPU software, developed in the UK since 2008 and delivered as a tutorial at ALIFE in 2018 and 2019. FLAME GPU 2 is an agent-based modelling simulation platform that enables modellers from various disciplines like economics, biology and social sciences to easily write agent-based models. Importantly, it abstracts the complexities of the GPU architecture away from modellers to ensure that modellers can concentrate on writing models without the need to acquire specialist knowledge typically required to utilise GPU architectures. This tutorial is aimed at the intermediate level. No knowledge of GPUs is required however basic knowledge multi agent modelling approaches is expected (i.e. formulating a problem as a set of individuals within a system) as well as a basic programming ability. The tutorial format is an introductory lecture followed by participants being provided the opportunity to complete a hands on exercise using the FLAME GPU software. Participants will be provided dedicated GPU cloud resources for interactively configuring and running a large scale agent based model within FLAME GPU. By the end of the practical session, it is expected that the participants will understand how to write and execute a multi-agent model for FLAME GPU from scratch. Participants will leave with an appreciation of the key techniques, concepts, and algorithms which have been used.