Numerical simulations of fluids in astrophysics and computational fluid dynamics (CFD) are among the most computationally-demanding calculations, in terms of sustained floating-point operations per second, or FLOP/s. It is expected that these numerical simulations will significantly benefit from the future Exascale computing infrastructures, that will perform 10^18 FLOP/s. The performance of the SPH codes is, in general, adversely impacted by several factors, such as multiple time-stepping, long-range interactions, and/or boundary conditions. In this work an extensive study of three SPH implementations SPHYNX, ChaNGa, and XXX is performed, to gain insights and to expose any limitations and characteristics of the codes. These codes are the starting point of an interdisciplinary co-design project, SPH-EXA, for the development of an Exascale-ready SPH mini-app. We implemented a rotating square patch as a joint test simulation for the three SPH codes and analyzed their performance on a modern HPC system, Piz Daint. The performance profiling and scalability analysis conducted on the three parent codes allowed to expose their performance issues, such as load imbalance, both in MPI and OpenMP. Two-level load balancing has been successfully applied to SPHYNX to overcome its load imbalance. The performance analysis shapes and drives the design of the SPH-EXA mini-app towards the use of efficient parallelization methods, fault-tolerance mechanisms, and load balancing approaches.
GaDE -- GPU-acceleration of time-dependent Dirac Equation for exascale
University of Bergen（卑尔根大学）；USIT, University of Oslo（奥斯陆大学信息科学与技术研究所）；Norwegian Research Infrastructure Services - NRIS（挪威研究基础设施服务）；The Arctic University of Norway（挪威北极大学）
Roadmap on Electronic Structure Codes in the Exascale Era
University of Michigan（密歇根大学）；SISSA-ISAS（的里雅斯特国际高等研究学校与材料系统分析研究所）；IOM-CNR（国家研究委员会凝聚态物理研究所）；Duke University（杜克大学）；London Centre for Nanotechnology（伦敦纳米技术中心）；National Institute for Materials Science（国立材料研究所）；Humboldt-Universität zu Berlin（柏林洪堡大学）；University of Texas at Austin（德克萨斯大学奥斯汀分校）；RIKEN Center for Computational Science（理化学研究所计算科学中心）；Pritzker School of Molecular Engineering, University of Chicago（芝加哥大学普立兹克分子工程学院）；Argonne National Laboratory（阿贡国家实验室）；Université Grenoble Alpes（格勒诺布尔阿尔卑斯大学）；University of Udine（乌迪内大学）；Université catholique de Louvain（天主教鲁汶大学）；University of Latvia（拉脱维亚大学）；University of California, Davis（加州大学戴维斯分校）；The Ohio State University（俄亥俄州立大学）；Materials Simulations from First Principles e.V. (MS1P)（第一性原理材料模拟协会）；Paderborn University（帕德博恩大学）；Indian Institute of Science（印度科学学院）；Lawrence Livermore National Laboratory（劳伦斯利弗莫尔国家实验室）；Centre for Computational Chemistry, School of Chemistry, University of Bristol（布里斯托尔大学化学学院计算化学中心）；Ames National Laboratory（艾姆斯国家实验室）；Iowa State University（爱荷华州立大学）；The NOMAD Laboratory at the FHI of the Max-Planck-Gesellschaft and IRIS Adlershof of the Humboldt Universität zu Berlin（马克斯·普朗克学会弗里茨·哈伯研究所NOMAD实验室及柏林洪堡大学IRIS阿德勒斯霍夫）；Max-Planck-Institute for the Structure and Dynamics of Matter（马克斯·普朗克物质结构与动力学研究所）
