Computational science is crucially important across diverse research communities from traditional topics in physics and chemistry to new applications in life and social sciences.
The drive to exascale computing, together with new computational paradigms in machine learning, artificial intelligence and big data present opportunities for science and society but also significant challenges for both traditional HPC and the new user communities.
This growing community requires increased computing power, new heterogeneous architecture paradigms, new software and new policies for resource access while benchmarks like High-Performance Linpack are becoming less and less representative of the computing ecosystems. Although new hardware solutions are emerging, computers become fatter, not faster, and exploiting the coming exascale systems remains a challenge for many traditional HPC applications.
The conference aims to open discussions on these new challenges, explore problems and propose solutions to address them and shape the future of scientific computing.