PASC

The increasing use of stochastic models for describing complex phenomena warrants surrogate models that capture the reference model characteristics at a fraction of the computational cost, foregoing the potentially expensive Monte Carlo simulation. The ...

Weather fronts play an important role in atmospheric science. Their correlation to severe natural hazards such as extreme precipitation, cyclones or thunderstorms makes localization and understanding of frontal systems an important factor in weather ...

Hardware accelerators are used to speed up computationally expensive applications in many scientific fields. However, offloading tasks to accelerator cards requires data to be transferred between the memory of the host and the external memory of the ...

This work introduces a new matrix decomposition, that we termed arrowhead factorization (AF). We showcase its applications as a novel method to compute all eigenvalues and eigenvectors of certain symmetric real matrices in the class of generalized ...

In computational fluid dynamics, the Boussinesq approximation is a popular model for the numerical simulation of natural convection problems. Although using the Boussinesq approximation leads to significant performance gains over a full-fledged ...

Numerical models of the ocean and ice sheets are crucial for understanding and simulating the impact of greenhouse gases on the global climate. Oceanic processes affect phenomena such as hurricanes, extreme precipitation, and droughts. Ocean models rely ...

In compiler theory, data analysis is used to exploit Instruction Level Parallelism (ILP). Three dependencies are used in modern compilers and hardware schemes efficiently and are fundamental to any code compilation. Read-after-read (RAR) has been left ...

This work presents the development, performance analysis and subsequent optimization of a GPU-based spectral hyperviscosity solver for turbulent flows described by the three dimensional incompressible Navier-Stokes equations. The method solves for the ...

We present a massively parallel lockstep algorithm for dualizing large numbers of surface triangulation graphs, and an effective implementation for CPU, GPU and multi-GPU. The algorithm is fully combinatorial, i.e., it does not require or use a planar or ...

The cryosphere plays a significant role in Earth's climate system. Therefore, an accurate simulation of sea ice is of great importance to improve climate projections. To enable higher resolution simulations, graphics processing units (GPUs) have become ...

In order to make the best use of the diverse hardware architectures in present and future high-performance computers, developers and maintainers of scientific simulation codes strive for performance portability. The goal is to reach a good fraction of ...

Operational Numerical Weather Prediction (NWP) workflows are highly data-intensive. Data volumes have increased by many orders of magnitude over the last 40 years, and are expected to continue to do so, especially given the upcoming adoption of Machine ...

The inclusion of atmospheric chemistry in global climate projections is currently limited by the high computational expense of modelling the many reactions of chemical species. Recent rapid advancements in artificial intelligence (AI) provide us with new ...

This paper presents two new hybrid MPI-GPU algorithms for building distributed octrees. The first algorithm redistributes data between processes and is used to globally sort the points on which the octree is generated, according to their SFC codes. The ...

This paper discusses parallel algorithms for computing intersections between pairs of meshes. We used parallel intersection algorithms to compute interpolation weights in coupled solvers which are part of multi-physics simulations. We present a parallel ...

Historically, temperature boundary conditions in thermal fluids have conventionally been approached as Robin-type boundary conditions. However, with the emergence of supercomputing capabilities, there is now the opportunity to explore the solution of ...

In recent years, we have witnessed the emergence of scientific machine learning as a data-driven tool for the analysis, by means of deep-learning techniques, of data produced by computational science and engineering applications.

At the core of these ...

In this paper, we present a thorough performance analysis of a highly parallel Monte Carlo code for modeling global erosion and redeposition in fusion devices, ERO2.0. The study shows that the main bottleneck preventing the code from efficiently using ...

Excited electronic states of molecules and solids play a fundamental role in fields such as catalysis and electronics. In electronic structure calculations, excited states typically correspond to saddle points on the surface described by the variation of ...

Tensor decompositions have emerged as powerful tools of multivariate data analysis, providing the foundation of numerous analysis methods. The Tucker decomposition in particular has been shown to be quite effective at compressing high-dimensional ...

With the growing adoption of AI-based systems across everyday life, the need to understand their decision-making mechanisms is correspondingly increasing. The level at which we can trust the statistical inferences made from AI-based decision systems is ...

We solve the 3D acoustic wave equation using the finite-difference time-domain (FDTD) formulation in both first and second order. The FDTD approach is expressed as a stencil-based computational scheme with a long-range discretization, i.e., 8^th order in ...

Particle accelerator modeling is an important field of research and development, essential to investigating, designing and operating some of the most complex scientific devices ever built. Kinetic simulations of relativistic, charged particle beams and ...

In numerical weather prediction and high-performance computing, the primary computational bottleneck has gradually evolved from floating-point arithmetic to the throughput of data to and from the storage. This phenomenon is commonly referred to as the I/...

In the era of extreme-scale computing, large-scale data storage and analysis have become more critical and challenging. For postprocessing, the simulation first needs to dump snapshots on a hard disk before processing any data. This becomes a bottleneck ...

The Cloud Model version 1 is an atmospheric model that allows for idealized studies of atmospheric phenomena. A new Lagrangian microphysics capability has been added, enabling a significantly more accurate representation than the traditional bulk or ...