54 citations · 115 across the 19 of their papers we have counts for
8 papers · 1 filter
Strong Scaling of OpenACC enabled Nek5000 on several GPU based HPC systems
Jonathan Vincent, Jing Gong, Martin Karp +11
We present new results on the strong parallel scaling for the OpenACC-accelerated implementation of the high-order spectral element fluid dynamics solver Nek5000. The test case con…
Higgs Boson Classification: Brain-inspired BCPNN Learning with StreamBrain
Martin Svedin, Artur Podobas, Steven W. D. Chien +1
One of the most promising approaches for data analysis and exploration of large data sets is Machine Learning techniques that are inspired by brain models. Such methods use alterna…
A High-Fidelity Flow Solver for Unstructured Meshes on Field-Programmable Gate Arrays
Martin Karp, Artur Podobas, Tobias Kenter +4
The impending termination of Moore's law motivates the search for new forms of computing to continue the performance scaling we have grown accustomed to. Among the many emerging Po…
A Deep Learning-Based Particle-in-Cell Method for Plasma Simulations
Xavier Aguilar, Stefano Markidis
We design and develop a new Particle-in-Cell (PIC) method for plasma simulations using Deep-Learning (DL) to calculate the electric field from the electron phase space. We train a…
Neko: A Modern, Portable, and Scalable Framework for High-Fidelity Computational Fluid Dynamics
Niclas Jansson, Martin Karp, Artur Podobas +2
Recent trends and advancement in including more diverse and heterogeneous hardware in High-Performance Computing is challenging software developers in their pursuit for good perfor…
StreamBrain: An HPC Framework for Brain-like Neural Networks on CPUs, GPUs and FPGAs
Artur Podobas, Martin Svedin, Steven W. D. Chien +5
The modern deep learning method based on backpropagation has surged in popularity and has been used in multiple domains and application areas. At the same time, there are other --…