gevolution 2.0：用于宇宙学的GPU加速相对论性N体模拟
gevolution 2.0: GPU-accelerated relativistic N-body simulations for cosmology
AI总结：
研究针对宇宙学的相对论性N体模拟，核心方法是对gevolution代码进行重大改进，采用三层并行化，包括MPI、OpenMP及CUDA，实现GPU加速，主要贡献是发布gevolution 2.0及GPU就绪版LATfield2库并展示性能基准。
AI中文摘要：
高性能计算越来越多地由使用图形处理单元（GPU）的硬件加速主导。为利用这一长期趋势，我们对相对论性粒子网格N体代码gevolution中的并行化方法进行了重大改进。新版本gevolution 2.0采用三层并行化：MPI用于分布式内存系统的可扩展性，在每个MPI等级上使用OpenMP进行共享内存并行化，以及使用CUDA将所有计算密集型任务卸载到GPU。该代码还包括过去几年开发的许多新功能。我们概述了代码结构并展示了关键性能基准。gevolution 2.0的公开发布可在该https URL找到。我们还发布了提供并行化后端的LATfield2库的GPU就绪版本，可在该https URL获取。
英文摘要：
High-performance computing is increasingly dominated by hardware acceleration using Graphics Processing Units (GPUs). To take advantage of this long-term trend, we implement a major overhaul of the parallelisation approach in the relativistic particle-mesh N-body code gevolution. The new version 2.0 of gevolution employs three layers of parallelisation: MPI for scalability on a distributed memory system, shared memory parallelisation on each MPI rank using OpenMP, and offloading all compute intensive tasks to GPUs using CUDA. The code also includes many new features that have been developed over the past years. We provide an overview of the code structure and show key performance benchmarks. The public release of gevolution 2.0 can be found at https://github.com/gevolution-code/gevolution-2.0. We also release a GPU-ready version of the LATfield2 library which provides the parallelisation backend, available at https://github.com/gevolution-code/LATfield2.
