ENCCS is supporting the development of key scientific HPC software in Sweden and providing consultancy and training to adapt the software to forthcoming (pre) exascale EuroHPC systems. On this page you can find more information on the core software packages we are supporting – ranging from molecular dynamics and electronic structure to climate modeling and computational fluid dynamics codes. ENCCS is also engaged in several machine-learning projects, including with industrial and public-sector partners.
In our work we draw on extensive individual experience in scientific computing and HPC software development which spans many programming languages, parallelization schemes and hardware architectures. We aim to strictly follow and train
best practices in software development – this includes using version control systems, automated testing, code coverage analysis and continuous integration as well as writing high-quality documentation, adhering to standard coding
styles and using well known build systems. We also strive to follow
FAIR software principles.
ENCCS is also in tight collaboration with Centres of Excellence (CoE) and can assist users get information on their supported software as well as get in touch with key people to get the support that they need. Click on the button below for more information.
GROMACS is a versatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles. It is primarily designed for biochemical molecules like proteins, lipids and nucleic acids that have a lot of complicated bonded interactions, but since GROMACS is extremely fast at calculating the nonbonded interactions (that usually dominate simulations) many groups are also using it for research on non-biological systems, e.g. polymers.
VeloxChem solves the Schrödinger equation to study the electronic structure of molecular systems. The program can compute molecular energies and simulate the response of molecules subject to external electromagnetic fields. VeloxChem is built to exploit the aggregate resources of computing systems: from laptops to clusters. It can handle thousands of atoms and leverages a hybrid Python/C++ programming paradigm for fast development without sacrificing performance
Nek5000 is an open-source code for the simulation of incompressible flow. Nek5000 is widely used in a broad range of applications, including the study of thermal hydraulics in nuclear reactor cores, the modeling of ocean currents and the simulation of combustion in mechanical engines. The Nek5000 discretization scheme is based on the spectral-element method. In this approach, the incompressible Navier-Stokes equations are discretized in space by using high-order, weighted residual techniques employing tensor-product polynomial bases.
ICON is a highly versatile next-generation global climate model. The model solves the equations of motion for the atmosphere and ocean and couple these together with unresolved processes such as small scale turbulence, cloud microphysics and radiation. The model code has been designed with parallelization in mind allowing scientists to achieve unprecedented kilometer-scale resolutions, enabling simulations of individual clouds and ocean eddies even on global grids.
Machine Learning Projects
Swedish language models
With RISE ( https://www.ri.se/en), ENCCS is helping build the next generation of Swedish language models from the BERT family. Currently we are training a DeBERTa-large model for Swedish with only a small amount of data by using transfer learning from the equivalent English models. This project is running as a pilot access in the early life of the BerzeLiUS AI supercomputer ( https://www.nsc.liu.se/systems/berzelius/).
Swedish speech synthesis
With Voxo AB ( https://www.voxo.ai/), ENCCS is using machine learning to develop Swedish-language speech-synthesis machine-learning models based on the Tacotron2 family of speech-synthesis model architectures. It will be a key component of Voxo’s conversational assistant capable of providing information in real time in response to spoken natural-language questions. It will be capable of learning to pronounce jargon relevant to particular domains, such as banking. It will generate audio streams quickly, so that users will be comfortable with natural conversation flow, without pauses for generating long replies. This project is using HPC time awarded via the PRACE SHAPE project (https://prace-ri.eu/hpc-access/shape-access/) on the German GPU-boosted supercomputer JUWELS ( https://www.fz-juelich.de/ias/jsc/EN/Home/home_node.html).
ESSENSE is a research code for flow calculations by solving the compressible Navier-Stokes equations. Using a high order finite difference method in combination with summation-by-parts operators and weak boundary conditions makes it possible to efficiently and reliably handle large problems on structured grids for reasonably smooth geometries.
EC-Earth is a global climate model system based on the idea to use the world-leading weather forecast model of the ECMWF (European Centre of Medium Range Weather Forecast) in its seasonal prediction configuration as the base of climate model. The model system can be used in several configurations including the classical climate model (atmosphere, soil, ocean, sea ice) and Earth System configurations (adding atmospheric chemistry and aerosols, ocean bio-geo-chemistry, dynamic vegetation and a Greenland ice sheet). The model is developed by the European EC-Earth consortium with SMHI as core partner leading the development and other Swedish partners from the universities of Lund, Stockholm, Gothenburg and Uppsala. The model in its different configurations and resolutions is used for climate change projections, predictions and process studies.