126 citations · 281 across the 27 of their papers we have counts for
27 papers
TERRA-NG v1.0: Extreme-Scale, GPU-accelerated Mantle Convection
Fabian Böhm, Nils Kohl, Ponsuganth Ilangovan +7
We present TERRA-NG, a portable, GPU-accelerated, matrix-free mantle-convection code. A single Kokkos C++ implementation runs at scale on NVIDIA, AMD, and Intel GPU supercomputers.…
Performance Analysis of Low-Order, GPU-accelerated Finite Element Kernels using Kokkos
Fabian Böhm, Nils Kohl, Harald Köstler +1
We study performance portability for low-order, matrix-free finite element kernels, using the example of a vectorial, variable-coefficient PDE operator originating in geophysical m…
Move the Query, Not the Cache: Characterizing Cross-Instance Latent Attention Redistribution Across GPU Fabrics
Bole Ma, Jan Eitzinger, Harald Köstler +1
Frontier LLMs increasingly decide what a query attends to with a sparse-attention indexer that picks a few KV-cache blocks per query: attention's unit is now a small, reusable chun…
Diagnosing Overhead in Dispatch Operations: Cross-architecture Observatory
Bole Ma, Jan Eitzinger, Harald Koestler +1
AlltoAll dispatch is the dominant bottleneck of MoE expert parallelism, and the interconnect community has responded with four families of mitigations: predictive sample placement,…
Benchmarking Convolutional Neural Network and Graph Neural Network based Surrogate Models on a Real-World Car External Aerodynamics Dataset
Sam Jacob Jacob, Markus Mrosek, Carsten Othmer +1
Aerodynamic optimization is crucial for developing eco-friendly, aerodynamic, and stylish cars, which requires close collaboration between aerodynamicists and stylists, a collabora…
Architecture Specific Generation of Large Scale Lattice Boltzmann Methods for Sparse Complex Geometries
Philipp Suffa, Markus Holzer, Harald Köstler +1
We implement and analyse a sparse / indirect-addressing data structure for the Lattice Boltzmann Method to support efficient compute kernels for fluid dynamics problems with a high…
Code Generation and Performance Engineering for Matrix-Free Finite Element Methods on Hybrid Tetrahedral Grids
Fabian Böhm, Daniel Bauer, Nils Kohl +5
This paper introduces a code generator designed for node-level optimized, extreme-scalable, matrix-free finite element operators on hybrid tetrahedral grids. It optimizes the local…
A Continuous Benchmarking Infrastructure for High-Performance Computing Applications
Christoph Alt, Martin Lanser, Jonas Plewinski +5
For scientific software, especially those used for large-scale simulations, achieving good performance and efficiently using the available hardware resources is essential. It is im…
Towards Code Generation for Octree-Based Multigrid Solvers
Richard Angersbach, Sebastian Kuckuck, Harald Köstler
This paper presents a novel method designed to generate multigrid solvers optimized for octree-based software frameworks. Our approach focuses on accurately capturing local feature…
waLBerla-wind: a lattice-Boltzmann-based high-performance flow solver for wind energy applications
Helen Schottenhamml, Ani Anciaux-Sedrakian, Frédéric Blondel +2
This article presents the development of a new wind turbine simulation software to study wake flow physics. To this end, the design and development of waLBerla-wind, a new simulato…
p-adaptive discontinuous Galerkin method for the shallow water equations on heterogeneous computing architectures
Sara Faghih-Naini, Vadym Aizinger, Sebastian Kuckuk +2
Heterogeneous computing and exploiting integrated CPU-GPU architectures has become a clear current trend since the flattening of Moore's Law. In this work, we propose a numerical a…
AI Driven Near Real-time Locational Marginal Pricing Method: A Feasibility and Robustness Study
Naga Venkata Sai Jitin Jami, Juraj Kardoš, Olaf Schenk +1
Accurate price predictions are essential for market participants in order to optimize their operational schedules and bidding strategies, especially in the current context where el…
Efficiency and scalability of fully-resolved fluid-particle simulations on heterogeneous CPU-GPU architectures
Samuel Kemmler, Christoph Rettinger, Ulrich Rüde +2
Current supercomputers often have a heterogeneous architecture using both CPUs and GPUs. At the same time, numerical simulation tasks frequently involve multiphysics scenarios whos…
MD-Bench: Engineering the in-core performance of short-range molecular dynamics kernels from state-of-the-art simulation packages
Rafael Ravedutti Lucio Machado, Jan Eitzinger, Jan Laukemann +3
Molecular dynamics (MD) simulations provide considerable benefits for the investigation and experimentation of systems at atomic level. Their usage is widespread into several resea…
Particle-resolved simulation of antidunes in free-surface flows
Christoph Schwarzmeier, Christoph Rettinger, Samuel Kemmler +5
The interaction of supercritical turbulent flows with granular sediment beds is challenging to study both experimentally and numerically; this challenging task has hampered the adv…
MD-Bench: A generic proxy-app toolbox for state-of-the-art molecular dynamics algorithms
Rafael Ravedutti Lucio Machado, Jan Eitzinger, Harald Köstler +1
Proxy-apps, or mini-apps, are simple self-contained benchmark codes with performance-relevant kernels extracted from real applications. Initially used to facilitate software-hardwa…
Deep Learning for Real-Time Aerodynamic Evaluations of Arbitrary Vehicle Shapes
Sam Jacob Jacob, Markus Mrosek, Carsten Othmer +1
The aerodynamic optimization process of cars requires multiple iterations between aerodynamicists and stylists. Response Surface Modeling and Reduced-Order Modeling are commonly us…
Known Operator Learning and Hybrid Machine Learning in Medical Imaging -- A Review of the Past, the Present, and the Future
Andreas Maier, Harald Köstler, Marco Heisig +2
In this article, we perform a review of the state-of-the-art of hybrid machine learning in medical imaging. We start with a short summary of the general developments of the past in…
lbmpy: Automatic code generation for efficient parallel lattice Boltzmann methods
Martin Bauer, Harald Köstler, Ulrich Rüde
Lattice Boltzmann methods are a popular mesoscopic alternative to macroscopic computational fluid dynamics solvers. Many variants have been developed that vary in complexity, accur…
Optimizing Geometric Multigrid Methods with Evolutionary Computation
Jonas Schmitt, Sebastian Kuckuk, Harald Köstler
For many linear and nonlinear systems that arise from the discretization of partial differential equations the construction of an efficient multigrid solver is a challenging task.…
waLBerla: A block-structured high-performance framework for multiphysics simulations
Martin Bauer, Sebastian Eibl, Christian Godenschwager +8
Programming current supercomputers efficiently is a challenging task. Multiple levels of parallelism on the core, on the compute node, and between nodes need to be exploited to mak…
Lattice Boltzmann Benchmark Kernels as a Testbed for Performance Analysis
Markus Wittmann, Viktor Haag, Thomas Zeiser +2
Lattice Boltzmann methods (LBM) are an important part of current computational fluid dynamics (CFD). They allow easy implementations and boundary handling. However, competitive tim…
Microswimming with inertia
Jayant Pande, Kristina Pickl, Oleg Trosman +2
Microswimmers, especially in theoretical treatments, are generally taken to be completely inertia-free, since inertial effects on their motion are typically small and assuming thei…
A Python Extension for the Massively Parallel Multiphysics Simulation Framework waLBerla
Martin Bauer, Florian Schornbaum, Christian Godenschwager +4
We present a Python extension to the massively parallel HPC simulation toolkit waLBerla. waLBerla is a framework for stencil based algorithms operating on block-structured grids, w…