Publication
Fast bio-inspired computation using a GPU-based systemic computer
AbstractBiology is inherently parallel. Models of biological systems and bio-inspired algorithms also share this parallelism, although most are simulated on serial computers. Previous work created the systemic computer – a new model of computation designed to exploit many natural properties observed in biological systems, including parallelism. The approach has been proven through two existing implementations and many biological models and visualizations. However to date the systemic computer implementations have all been sequential simulations that do not exploit the true potential of the model. In this paper the first ever parallel implementation of systemic computation is introduced. The GPU Systemic Computation Architecture is the first implementation that enables parallel systemic computation by exploiting the multiple cores available in graphics processors. Comparisons with the serial implementation when running two programs at different scales show that as the number of systems increases, the parallel architecture is several hundred times faster than the existing implementations, making it feasible to investigate systemic models of more complex biological systems.
Download publicationAssociated Researchers
Related Resources
See what’s new.
2012
Housing Agency System: Mass-Customization System for Housing
The field of architecture and houses demands a radical re-invention of…
2002
StyleCam: Interactive Stylized 3D Navigation using Integrated Spatial & Temporal Controls
We describe a new type of graphical user interface widget, known as a…
2022
It’s Over There: Designing an Intelligent Virtual Agent That Can Point Accurately into the Real World
It is challenging to design an intelligent virtual agent (IVA) that…
2012
User Experience and Likelihood to Recommend: Linking UX and Net Promoter Score
This study reports on a two-year survey in which user experience…
Get in touch
Something pique your interest? Get in touch if you’d like to learn more about Autodesk Research, our projects, people, and potential collaboration opportunities.
Contact us