First GPU Computing Seminar - Towards achieving GPU-native adaptive mesh refinement


We've kicked off our first GPU Computing group seminar this year with a talk by Ania Brown from Oxford e-Research Centre titled "Towards achieving GPU-native adaptive mesh refinement" on 30th of May 2017. Adaptive mesh refinement (AMR) is a method for reducing memory cost by varying the accuracy in each region to match the physical characteristics of the simulation, at the cost of increased data structure complexity. Ania described the optimisation and software challenges that need to be considered when implementing AMR on GPUs, based on her experience working on a GPU-native framework for stencil calculations on a tree-based adaptively refined mesh as part of her Master degree.

There's no offical GPU Computing talks in June but we highly recommend the upcoming talk "From Democratic Consensus to Cannibalistic Hordes: The Principles of Collective Animal Behaviour" by Prof. Iain Couzin on the 29th of June 2017.

Links and More Information

For presentation slides and more information on both of these talks, visit the GPU Computing seminars page.