document

GPU-Accelerated Atmospheric Large Eddy Simulation: Preparing DALES for the Exascale Era

Jungbacker, Caspar (author)

Large Eddy Simulation (LES) is a mathematical technique for performing simulations of turbulent flows, such as those found in the Earth’s atmosphere. Compared to traditional numerical weather and climate models, LES is more accurate in representing turbulent processes and cloud dynamics. The computational burden of LES, however, have histor-...

master thesis 2024

document

Interface-resolved simulations of dense particulate flows: Studies on sedimentation and slurry pipe flow

Shajahan, M.T. (author)

Dense suspension flows, both in the natural environment and industrial settings, are complex phenomena with significant implications. From rivers shaping landscapes to industrial processes involving slurry transport, these flows hold a prominent position in numerous sectors. This thesis delves into a specific facet of these intricate flows:...

doctoral thesis 2024

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Optimizing the Cost and Performance for Batch jobs on HPC by Utilizing Swap Space

Lin, Hanzhang (author)

High Performance Computing (HPC) facilities play a crucial role in acceler- ating Electronic Design Automation (EDA) procedures at NXP Semiconduct- ors. The increasing number of job requests and workloads has led to a surge in memory demand, which is a costly resource. To address this, we leverage memory swap space on disk as a more affordable...

master thesis 2023

document

Computing Resonant States of a Quantum Mechanical Three-body Problem on Supercomputers

Meng, Zhaonan (author)

This thesis aims to develop an advanced numerical solver capable of efficiently computing the resonant states of quantum mechanical two-body and three-body problems, thereby expanding our understanding of these complex systems. The quantum three-body problems feature at least two dimensions, which necessitates substantial computational efforts....

master thesis 2023

document

Oikonomos-II: A Reinforcement-Learning, Resource-Recommendation System for Cloud HPC

Betting, J. L. F. (author), Zeeuw, C. I. De (author), Strydis, C. (author)

The cloud has become a powerful and useful environment for the deployment of High-Performance Computing (HPC) applications, but the large number of available instance types poses a challenge in selecting the optimal platform. Users often do not have the time or knowledge necessary to make an optimal choice. Recommender systems have been...

conference paper 2023

document

Parareal Method for Anisotropic Diffusion Denoising

Shan, X. (author), van Gijzen, M.B. (author)

This paper studies time-domain parallelisation using Parareal to speed up the computations of anisotropic diffusion filtering. We consider both explicit and implicit Euler based method for the propagation in time for Parareal. The Preconditioned Conjugate Gradient (PCG) method is used to solve the systems that arise in the implicit based...

conference paper 2023

document

SIMD vectorization for simultaneous solution of locally varying linear systems with multiple right-hand sides

Kühn, Martin J. (author), Holke, Johannes (author), Lutz, Annette (author), Thies, J. (author), Röhrig-Zöllner, Melven (author), Bleh, Alexander (author), Backhaus, Jan (author), Basermann, Achim (author)

Developments in numerical simulation of flows and high-performance computing influence one another. More detailed simulation methods create a permanent need for more computational power, while new hardware developments often require changes to the software to exploit new hardware features. This dependency is very pronounced in the case of...

journal article 2023

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Containerization for High Performance Computing

Eijsvogel, Nienke (author)

Containerization, a lightweight form of virtualization, increasingly became more popular in the last decade. Containers can offer a level of isolation and privacy to the user, which are not always sought after. High performance computing workloads benefit from having a custom container filesystem, but would suffer from any overhead incurred by...

master thesis 2022

document

EDEN: A High-Performance, General-Purpose, NeuroML-Based Neural Simulator

Panagiotou, S. (author), Sidiropoulos, Harry (author), Soudris, Dimitrios (author), Negrello, Mario (author), Strydis, C. (author)

Modern neuroscience employs in silico experimentation on ever-increasing and more detailed neural networks. The high modeling detail goes hand in hand with the need for high model reproducibility, reusability and transparency. Besides, the size of the models and the long timescales under study mandate the use of a simulation system with high...

journal article 2022

document

Parallel Scalability of Three-Level FROSch Preconditioners to 220000 Cores using the Theta Supercomputer

Heinlein, A. (author), Rheinbach, Oliver (author), Röver, Friederike (author)

The parallel performance of the three-level fast and robust overlapping Schwarz (FROSch) preconditioners is investigated for linear elasticity. The FROSch framework is part of the Trilinos software library and contains a parallel implementation of different preconditioners with energy minimizing coarse spaces of generalized Dryja--Smith--Widlund...

journal article 2022

document

performance of the low-rank TT-SVD for large dense tensors on modern multicore CPUs

Röhrig-Zöllner, Melven (author), Thies, J. (author), Basermann, Achim (author)

There are several factorizations of multidimensional tensors into lower-dimensional components, known as ``tensor networks."" We consider the popular ``tensor-train"" (TT) format and ask, How efficiently can we compute a low-rank approximation from a full tensor on current multicore CPUs? Compared to sparse and dense linear algebra, kernel...

journal article 2022

document

MFEM: A modular finite element methods library

Anderson, Robert (author), Andrej, Julian (author), Barker, Andrew (author), Bramwell, Jamie (author), Camier, Jean Sylvain (author), Cerveny, Jakub (author), Dobrev, Veselin (author), Dudouit, Yohann (author), Akkerman, I. (author)

MFEM is an open-source, lightweight, flexible and scalable C++ library for modular finite element methods that features arbitrary high-order finite element meshes and spaces, support for a wide variety of discretization approaches and emphasis on usability, portability, and high-performance computing efficiency. MFEM's goal is to provide...

journal article 2021

document

Towards Real-Time Olivary Neuron Modeling

Nicou, Nikolas (author)

The field of Computing has been a significant catalyst for innovation across various segments of our lives. Computational neuroscience keeps demanding increased perfor- mance to implement powerful simulators able to closely approximate brain behavior using complex mathematical models. This resulted in various High-Performance Com- puting systems...

master thesis 2020

document

FDBB: Fluid dynamics building blocks

Möller, M. (author), Jaeschke, Andrzej (author)

High-performance computing platforms are becoming more and more heterogeneous, which makes it very difficult for researchers and scientific software developers to keep up with the rapid changes on the hardware market. In this paper, the open-source project FDBB (Fluid Dynamics Building Blocks) is presented, which eases the development of...

conference paper 2020

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Dark Data as the New Challenge for Big Data Science and the Introduction of the Scientific Data Officer

Schembera, Björn (author), Duran, J.M. (author)

Many studies in big data focus on the uses of data available to researchers, leaving without treatment data that is on the servers but of which researchers are unaware. We call this dark data, and in this article, we present and discuss it in the context of high-performance computing (HPC) facilities. To this end, we provide statistics of a...

journal article 2019

document

A conceptual framework for quantum accelerated automated design optimization

Möller, M. (author), Vuik, Cornelis (author)

The development of practical quantum computers that can be used to solve real-world problems is in full swing driven by the ambitious expectation that quantum supremacy will be able to outperform classical super-computers. Like with any emerging compute technology, it needs early adopters in the scientific computing community to identify...

journal article 2019

document

The Case for Polymorphic Registers in Dataflow Computing

Ciobanu, C.B. (author), Gaydadjiev, G. (author), Pilato, Christian (author), Sciuto, Donatella (author)

Heterogeneous systems are becoming increasingly popular, delivering high performance through hardware specialization. However, sequential data accesses may have a negative impact on performance. Data parallel solutions such as Polymorphic Register Files (PRFs) can potentially accelerate applications by facilitating high-speed, parallel access to...

journal article 2018

document

Moving workloads to a better place: Optimizing computer architectures for data-intensive applications

Vermij, E.P. (author)

The performance of supercomputers is not growing anymore at the rate it once used to. Several years ago a break with historical trends appeared. First the break appeared at the lower end of worldwide supercomputer installations, but now it affects a significant number of systems with average performance. Power consumption is becoming the most...

doctoral thesis 2017

document

Accelerating volcanic ash data assimilation using a mask-state algorithm based on an ensemble Kalman filter: A case study with the LOTOS-EUROS model (version 1.10)

Fu, Guangliang (author), Lin, H.X. (author), Heemink, A.W. (author), Lu, S. (author), Segers, Arjo (author), van Velzen, C. (author), Lu, Tongchao (author), Xu, Shiming (author)

In this study, we investigate a strategy to accelerate the data assimilation (DA) algorithm. Based on evaluations of the computational time, the analysis step of the assimilation turns out to be the most expensive part. After a study of the characteristics of the ensemble ash state, we propose a mask-state algorithm which records the sparsity...

journal article 2017

document

Improving volcanic ash forecasts with ensemble-based data assimilation

Fu, Guangliang (author)

The 2010 Eyjafjallajökull volcano eruption had serious consequences to civil aviation. This has initiated a lot of research on volcanic ash forecasting in recent years. For forecasting the volcanic ash transport after eruption onset, a volcanic ash transport and diffusion model (VATDM) needs to be run with Eruption Source Parameters (ESPs) such...

doctoral thesis 2017