27 datasets

ZivaHub + Deakin Research Online + DMU Figshare2026 · dataset · unknown

Graph algorithms find several usages in industry, science, humanities, and technology. The fast-growing size of graph datasets in the context of the processing model of the current hardware has resulted in different bottlenecks such as memory locality, work-efficiency, and load-balance that degrade the performance. To tackle these limitations, high-performance computing considers different aspects

ZivaHub + Deakin Research Online + DMU Figshare2026 · dataset · unknown

This thesis presents a theoretical study of the kaolin minerals carried out using previously unattainable levels of physics, enabled using machine learned interatomic potentials (MLIPs). The kaolin minerals represent systems which have evaded extensive computational study, due largely in part to the complex interlayer physics and large system sizes necessary to adequately compute properties of int

ZivaHub2026 · dataset

<p dir="ltr">This poster describes work on a deterministic workflow that created a set of tools and a set of MD vaults describing versions of the Message Passing Interface Standard from versions 1.3 to 5.x. In addition, a 'hypervault' that works longitudinally across the standard versions is provided.</p><p dir="ltr">The findings were used to demonstrate compliance of three implementations of MPI

figshare + Loughborough Research Repository2026 · Astronomical catalogue

<p dir="ltr">This dataset supports a study of <b>GPU power management, energy efficiency, and hardware-aware power prediction for deep-learning workloads</b>. The research characterizes five deep-learning architectures across NVIDIA Tesla T4 and Quadro GV100 GPUs, evaluates large-language-model-based GPU power predictions, and investigates the effects of hardware power capping on power consumption

Teesside University Research Data Repository2026 · dataset

Phase diagrams (PDs) illustrate the relative stability of competing phases under varying conditions, serving as critical tools for synthesizing complex materials. Reliable phase diagrams rely on precise free energy calculations, which are computationally intensive. We introduce exaPD, a user-friendly workflow that enables simultaneous sampling of multiple phases across a fine mesh of temperature a

DaRUS2026 · dataset · unknown

This dataset contains the case files for the two-scale heat conduction test case with adaptive model-switching on the micro scale that is part of Chapter 6 of the dissertation of Ishaan Desai.

e-cienciaDatos2026 · dataset · unknown

GPU-accelerated topology optimization pipeline written in Julia + CUDA, targeting large-scale 3D structural design problems on heterogeneous HPC clusters such as Madroño. The code implements the SIMP (Solid Isotropic Material with Penalization) formulation with Wang–Lazarov–Sigmund Heaviside projection, solved through a matrix-free multigrid-preconditioned conjugate gradient (PCG) elasticity solve

DaRUS2026 · dataset · unknown

This Dataset contains the scaling and single node performance data which corresponds to the Section 5: Performance Evaluation of the publication on GALÆXI v2.0 ([link to paper when available]).

DaRUS2026 · dataset · unknown

This Dataset contains the data produced by and for the recreation of runs of transonic flow over NACA64A-110 and OAT15A airfoils. The contained data corresponds to the Section6: Applications of the publication on GALÆXI v2.0 ([link to paper when available]). To recreate this data run "build.sh" in each sub-directory to clone and compile GALÆXI v2.0. The usage instructions for the "run.sh" scripts

DaRUS2026 · dataset · unknown

This Dataset contains the data used for the comparison of the thread data locality approaches for kernels in GALÆXI v2.0 which corresponds to the Section 3.2.2:Thread Level Parallelism of the publication on GALÆXI v2.0 ([link to paper when available]). The purpose of this data is to compare the performance of assigning GPU threads to either a single degree of freedom or a single face in algorithms

DaRUS2026 · dataset · unknown

This Dataset contains the data used for the validation of GALÆXI v2.0 which corresponds to the Section 4: Validation of the publication on GALÆXI v2.0 ([link to paper when available]). To recreate this data run "run.sh" in each sub-directory to clone and compile GALÆXI v2.0 and execute the code for the given case. The usage instructions for the "run.sh" scripts are available within the "run.sh" sc

DaRUS2026 · dataset · unknown

This dataset contains software (preCICE and ASTE) as well as setup and result files to reproduce the numerical experiments in Section 5.3 of my dissertation titled "Flexible and Efficient Data Mapping for Simulation of Coupled Problems". For further instructions on how to run the experiments see the README.md of the dataset.

figshare + Loughborough Research Repository2026 · Astronomical catalogue

<p dir="ltr">AlphaFold 3 (AF3) enables accurate biomolecular modeling, but CPU-bound multiple sequence alignment (MSA) construction can limit end-to-end throughput. We introduce AlphaFast, an integrated framework that combines batched MMseqs2-GPU homology search with AF3-compatible feature generation, model weights, and outputs. AlphaFast achieves a 68.5-fold speedup in data generation and a 22.8-

REDU - Unicamp Institutional Research Data Repository2025 · dataset · unknown

Execution scripts and artifacts necessary to reproduce experiments from the Master's dissertation entitled "Deep Learning Compilers for Signal Processing Kernel Generation". The scripts are a mixture of Python and Bash scripts, while the generated artifacts consists of search logs and object files generated by Apache TVM's Ansor seach, CSVs containing the execution time logs, and data slices from

DaRUS2025 · dataset · unknown

This dataset contains software (preCICE and ASTE) as well as setup and result files to reproduce the numerical experiments in Section 5.2 of my dissertation titled "Flexible and Efficient Data Mapping for Simulation of Coupled Problems". For further instructions on how to run the experiments see the README.md of the dataset.

figshare2025 · Astronomical catalogue

<p dir="ltr">Modern HPC platforms are using multiple CPU, GPUs and high-performance interconnects per node. Unfortunately, state-of-the-art production quality implementations of the popular Message Passing Interface (MPI) programming model do not have the appropriate support to deliver the best performance and scalability for applications (HPC and AI) on such systems.This project aims to investiga

Teesside University Research Data Repository2025 · dataset

We present quTARANG, a robust GPU-accelerated Python package developed for a comprehensive study of turbulence problems in Bose-Einstein condensates (BECs). It solves the mean-field Gross-Pitaevskii equation (GPE) using a Time-splitting pseudo-spectral (TSSP) scheme and ground state calculations are performed using a Backward Euler spectral (BESP) scheme. quTARANG also has post-processing tools th

REDU - Unicamp Institutional Research Data Repository2024 · dataset · unknown

GPUZIP v2.0 Reproducibility Dataset This dataset provides all the necessary materials to reproduce the results presented in the GPUZIP v2.0 article. It is organized into folders, each containing a README.md.txt file that describes its contents and explains how to interpret the files. Note:This dataset is organized as a directory structure, so for better visualization change the "View type" to "Tre

DaRUS2024 · dataset · unknown

This Dataset contains the setup data for the NASA Rotor 37 test case which corresponds to the application section in the GALÆXI Paper (Section 6). Reference (Link): L. Reid, R. D. Moore, Design and overall performance of four highly loaded, high speed inlet stages for an advanced high-pressure-ratio core compressor, Technical Report 1337, NASA Lewis Research Center, Cleveland, OH, United States, 1

DaRUS2024 · dataset · unknown

This Dataset contains the results of the scaling test cases of the GALÆXI Paper (Section 4). The scaling behavior is evaluated using simulations with resolutions ranging from 16384 up to 8.6x109 degrees of freedom using up to 1024 GPUs on JUWELS booster. The provided results contain the raw data of the performance index PID for different loads investigated. The results of the different PIDs are fu

DaRUS2024 · dataset · unknown

This Dataset contains the setup and the results of the convergence tests which are reported in the GALÆXI Paper (Section 5.1). The results are contained in the file results.txt. The used case is based on the method of manufactured solution. The detailed formulation is specified in Hindenlang et al. and is implemented as ExactFunc=4 in GALÆXI. The folder convtest/ contains the setup for the simulat

DaRUS2024 · dataset · unknown

This Dataset contains the test case definition and reference data for the Taylor-Green Vortex (TGV) test case which builds the validation test case in the GALÆXI Paper (Section 5). Incompressible TGV (Ma=0.1) according to (Link): J. DeBonis, Solutions of the Taylor–Green vortex problem using high- resolution explicit finite difference methods, in: 51st AIAA Aerospace Sciences Meeting, 2013, p. 382

DaRUS2022 · dataset · unknown

This data repository contains the REG-30 model for the GEO.KW project. The dataset contains the PFLOTRAN and urbs software and simulation setup. Instructions for building the spack environment and running the simulation are provided in the README.

DaRUS2022 · dataset · unknown

This data repository contains the COM-4 model for the GEO.KW project. The dataset contains the PFLOTRAN and urbs simulation setup, spack build environment and spack build mirror to replicate the software build environment. A README file is provided, explaining the spack building procedure and running the simulation.

Edmond2022 · Astronomical catalogue · unknown

This dataset contains the ICON code, the experiments run scripts, and the experiments time results and the derived scaling values, for the article: "Improving scalability of Earth System Models through coarse-grained component concurrency - a case study with the ICON v2.6.5 modelling system". Note that the ICON code is provided here only for documentation purposes of the above study. For any other