The exponential rise in the quantity of visual data that is currently being produced in both daily life and scientific research poses huge challenges in terms of processing and storage. The potential solution of using supercomputers is hampered by high costs and slow capacity growth. Distributed computing provides an attractive alternative that can be scaled on demand. Fangbin Liu explores how massively heterogeneous parallel distributed computing architectures can be applied to accelerate large-scale image processing applications effectively and efficiently.
F. Liu: High Performance Adaptive Image Processing on Multi-Scale Hybrid Architectures.
Prof. M. Worring
Dr A.L. Varbanescue
Dr F.J. Seinstra
This event is open to the public.