Software Environment for Actionable & VVUQ-evaluated Exascale Applications (SEAVEA)
Lead Research Organisation:
Brunel University London
Department Name: Computer Science
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Publications
Bhati AP
(2023)
Long Time Scale Ensemble Methods in Molecular Dynamics: Ligand-Protein Interactions and Allostery in SARS-CoV-2 Targets.
in Journal of chemical theory and computation
Shi Y
(2022)
A Latent Encoder Coupled Generative Adversarial Network (LE-GAN) for Efficient Hyperspectral Image Super-Resolution
in IEEE Transactions on Geoscience and Remote Sensing
Wan S
(2023)
Comparison of Equilibrium and Nonequilibrium Approaches for Relative Binding Free Energy Predictions
in Journal of Chemical Theory and Computation
Wan S
(2023)
Ensemble-Based Approaches Ensure Reliability and Reproducibility.
in Journal of chemical information and modeling
Zhang X
(2023)
CXR-Net: A Multitask Deep Learning Network for Explainable and Accurate Diagnosis of COVID-19 Pneumonia From Chest X-Ray Images.
in IEEE journal of biomedical and health informatics
| Title | FabSim3 |
| Description | FabSim3 is an automation toolkit for computational research. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | See paper. |
| URL | https://fabsim3.readthedocs.io |
| Description | Partnership with Save the Children in developing Flee 3.0 |
| Organisation | Save the Children UK |
| Country | United Kingdom |
| Sector | Charity/Non Profit |
| PI Contribution | We are incorporating a range of features into the Flee code and the associated FabFlee plugin, and are performing sensitivity analysis using the tools. |
| Collaborator Contribution | They test out the Flee code on a realistic setting, perform pre- and post-processing, and inform our assumptions. |
| Impact | This is a multi-disciplinary collaboration between computer science and the humanitarian sector. Several internal reports have been published so far. |
| Start Year | 2021 |
| Title | FabSim3 v3.6 |
| Description | FabSim3 is a Python-based automation toolkit for scientific simulation and data processing workflows, licensed under the BSD 3-clause license. Among other things, FabSim3 supports the use of simple one-liner commands to: Enable execution of simulation and analysis tasks on supercomputers. Establish and run coupled models using the workflow automation functionalities. Organize input, output and environment information, creating a consistent log and making it possible by default to repeat/reproduce runs. Perform large ensemble simulations (or replicated ones) using a one-liner command. Users can perform complex remote tasks from a local command-line, and run single jobs, ensembles of multiple jobs, and dynamic workflows through schedulers such as SLURM, PBSPro, LoadLeveller and QCG. FabSim3 stores machine-specific configurations in the repository, and applies it to all applications run on that machine. These configurations are updated by any contributor who feels that a fix or improvement is required. |
| Type Of Technology | Software |
| Year Produced | 2022 |
| Open Source License? | Yes |
| Impact | FabSim3 is in use across a range of EU and UK research projects. |
| URL | https://fabsim3.readthedocs.io/en/latest/ |
| Title | Flu And Coronavirus Simulator v2.0.0 |
| Description | FACS is an agent-based modelling code that models the spread of flu and coronaviruses in local regions. Up to now, we have used it to model the spread of Covid-19 in a range of London boroughs. The code can be repurposed to model other regions, and its current (sequential) implementation should be able to run up to 500,000 households within a reasonable time frame. It also supports vaccination programmes, track and trace and mutated versions of the virus. What sets FACS apart from many other codes is that we have a partially automated location extraction approach from OpenStreetMaps data (the scripts reside at https://www.github.com/djgroen/covid19-preprocess), that we resolve a wide range of different location types (e.g., supermarkets, offices, parks, schools, leisure locations and hospitals) and that we have a specific algorithm for modeling infections within these locations, taking into account the physical size of each location. V2.0.0 is the first version that supports parallel execution using MPI. |
| Type Of Technology | Software |
| Year Produced | 2022 |
| Open Source License? | Yes |
| Impact | FACS is in use across several trials in the EU-funded STAMINA project. |
| URL | https://facs.readthedocs.io |