Reliable software environments are often a problem for data scientists. This becomes an issue especially when the analysis needs to be run on different machines – colleagues laptop, cloud VM or HPC cluster. Here we introduce the idea of containerised [...]
Viking, the Scandinavian Online Kit for Nanoscale Modelling [1,2], is a highly convenient web-based graphical user interface application for computational chemistry or molecular dynmaics simulation. It allows users to configure their MD simulations in a [...]
Debugging is often an essential part of software development. In the scope of this tutorial, I will present a couple of tools with OpenFOAM as a practical example of a C+±based scientific simulation code. After a brief reminder aboute the [...]
In the realm of computational biology, GROMACS has emerged as a powerful tool for molecular dynamics simulations. Our service provides a detailed guide to setting up and running a GROMACS simulation workflow, complete with visualization using Visual Molecular Dynamics (VMD). [...]
As a domain scientist doing high-performance computing, you might find the need to code yourself. Be it that you need custom scripts for efficient file handling, extending the functionality of pre-existing software, or even coding a larger software project from [...]
The GWDG offers data scientists various services and training courses to support them in their work throughout their entire workflow. As the success of a machine learning project often depends on the available computing resources, the working group “Computing” operates [...]
As part of the BMBF founded project FORESTCARE we have developed SynForest, an application that generates high-quality point cloud datasets of synthetic forests. For this purpose, we aimed to produce realistic patterns by combining forest growth simulation tools such [...]
There are many python packages that are tightly integrated with Dask which enables parallel data processing. For instance, consider xarray package. This package is used to read datasets in netcdf, hdf5, zarr file formats. Dask comes in play when data [...]
When it comes to our High-Performance Computing (HPC) systems, efficiency is the name of the game. But are you managing your Python environments efficiently?
Our HPC systems use network file systems that are optimized to access a small number of [...]
Deep learning powers a broad range of applications, from autonomous cars and image generation to voice assistants. The successful training of deep learning models necessitates the use of graphics processing units (GPUs). To facilitate a quick and easy start with [...]
Quantum computers and their capabilities is an area of growing global interest and resource allocation. Particularly exciting is the possibility of exponential improvements in classical machine learning algorithms when executed by an equivalent algorithm on a quantum computer. GWDG, along [...]
VSCode is a popular lightweight IDE developed by Microsoft that supports many programming languages and scripts. There are many features and capabilities that can be added to VSCode by installing extensions from the marketplace, including the ability to develop [...]
An AI-based solution to one of the grand challenges in modern biology
“AlphaFold” is a word which may or may not sound familiar to you. It is an open-source, deep-learning application to predict protein structures, celebrated as a breakthrough to [...]
Four of our colleagues of AG Computing had a fantastic time at the PyCon DE & PyData Berlin 2023. During the three days at the conference, a diverse set of topics related to Python and data science was addressed. [...]
Switching from executing code locally to running it on a compute cluster can be a daunting and sometimes also confusing experience. This article provides a brief overview of fundamental concepts to efficiently run code on the [...]