66 PP16 Abstracts IP1
[email protected] Scalability of Sparse Direct Codes IP4 As part of the H2020 FET-HPC Project NLAFET, we are studying the scalability of algorithms and software for us- Next-Generation AMR ing direct methods for solving large sparse equations. We Block-structured adaptive mesh refinement (AMR) is a examine how techniques that work well for dense system powerful tool for improving the computational efficiency solution, for example communication avoiding strategies, and reducing the memory footprint of structured-grid nu- can be adapted for the sparse case. We also study the merical simulations. AMR techniques have been used for benefits of using standard run time systems to assist us in over 25 years to solve increasingly complex problems. I developing codes for extreme scale computers. We will look will give an overview of what we are doing in Berkeley at algorithms for solving both sparse symmetric indefinite Labs AMR framework, BoxLib, to address the challenges systems and unsymmetric systems. of next-generation multicore architectures and the com- plexity of multiscale, multiphysics problems, including new Iain Duff ways of thinking about multilevel algorithms and new ap- Rutherford Appleton Laboratory, Oxfordshire, UK OX11 proaches to data layout and load balancing, in situ and 0QX in transit visualization and analytics, and run-time perfor- and CERFACS, Toulouse, France mance modeling and control. iain.duff@stfc.ac.uk Ann S. Almgren Lawrence Berkeley National Laboratory IP2
[email protected] Towards Solving Coupled Flow Problems at the Ex- treme Scale IP5 Scalability is only a necessary prerequisite for extreme scale Beating Heart Simulation Based on a Stochastic computing.