Lukas Arnold

A massively parallel, multi-disciplinary Barnes-Hut tree code for extreme-scale N-body simulations

The efficient parallelization of fast multipole-based algorithms for the N-body problem is one of the most challenging topics in high performance scientific computing. The emergence of non-local, irregular communication patterns generated by these algorithms can easily create an insurmountable bottleneck on supercomputers with hundreds of thousands of cores. To overcome this obstacle we have developed an innovative parallelization strategy for Barnes–Hut tree codes on present and upcoming HPC multicore architectures. This scheme, based on a combined MPI–Pthreads approach, permits an efficient overlap of computation and data exchange. We highlight the capabilities of this method on the full IBM Blue Gene/P system JUGENE at Julich Supercomputing Centre and demonstrate scaling across 294,912 cores with up to 2,048,000,000 particles. Applying our implementation pepc to laser–plasma interaction and vortex particle methods close to the continuum limit, we demonstrate its potential for ground-breaking advances in large-scale particle simulations.

Progress in Mesh-Free Plasma Simulation With Parallel Tree Codes

The recent developments in mesh-free plasma modeling using parallel tree codes are described, covering the algorithmic and performance issues and how to apply this technique to multidimensional electrostatic plasma problems. Examples of the simulations of the ion acceleration by high-intensity lasers, heating, and the dynamics of the nanostructured targets, as well as more recent applications of this technique to the simulations of edge plasmas in tokamaks and mesh-free magnetoinductive models, are given.

Towards a petascale tree code: Scaling and efficiency of the PEPC library

Abstract The highly scalable parallel tree code PEPC for rapid computation of long-range (1/ r ) Coulomb forces is presented. It can be used as a library for applications involving electrostatics or Newtonian gravity in 3D. The code is based on the hashed oct-tree algorithm, in which particle coordinates are projected onto a space-filling curve prior to sorting and construction of multipole moments. However, standard particle sorting techniques can ultimately limit the scalability of such algorithms for thousands of cores, a bottleneck which can be alleviated by a recursive sort scheme specially adapted to the Morton curve. More serious limitations of the original locally essential tree concept of Salmon and Warren, which ultimately lead to a failure in memory scaling, are identified and analyzed rigorously. Benchmarks for the code on the IBM Blue Gene/P Jugene are presented which demonstrate scaling for multi-million particle systems on up to 8192 cores.

Performance Portability Analysis for Real-Time Simulations of Smoke Propagation Using OpenACC

Real-time simulations of smoke propagation during fires in complex geometries challenge engineers, physicists, mathematicians and computer scientists due to the complexity of fluid dynamics and the large number of involved physical and chemical processes. Recently, several application scenarios emerged that require real-time predictions during an incident to support the rescue teams. Therefore, we develop the CFD-based simulation software JuROr aiming to run in real-time by leveraging parallel computer architectures like CPUs and GPUs. For that, we parallelize the code with OpenACC directives that promise maintenance of a single source base by delegating some architecture-agnostic optimizations to the compiler. We investigate the performance portability of JuROr using PGI’s OpenACC implementation across four Intel CPUs and three NVIDIA GPUs. We present the achieved performance shares as part of a roofline model where we focus on traditionally-computed arithmetic code intensities, as well as on a measurement approach based on performance counters.