Welcome to Advanced Research Computing @ Cardiff (ARCCA).
ARCCA is a division within Cardiff University which provides, co-ordinates, supports and develops advanced research computing services for University researchers.
ARCCA also works with clients and partners outside the University through a range of outreach activities.
What is Advanced Research Computing?
Advanced Research Computing is a hugely powerful technique which is enabling and enhancing research in more than half of the University's academic Schools.
Broadly, we define Advanced Research Computing to be the use of computing and data resources for research, which are beyond the capabilities of the average desktop or laptop computer. Typically, this technique uses leading-edge IT resources and tools to pursue research; including computer simulation and modelling, manipulating and storing large amounts of data, and many other methods to solve research problems that would otherwise be impossible.
If your research has the potential to use these techniques, or even if you are just curious to find out more, please get in touch. We would be delighted to discuss what advanced research computing means in practice, and how ARCCA may be able to help you to do your computer-processing based research much more effectively. We also provide introductory training sessions aimed at any interested staff and postgraduates within the University.
Compelling applications for Advanced Research Computing
We provide below just some of the application areas that stand to benefit from Advanced Research Computing. In addition to furthering basic scientific understanding, most of these applications have clear practical benefits. This is a far from complete list, but it does represent their broad range and complexity. In addition to involving large and complex simulations, each area is characterised to varying degrees by the deployment of variety of computing techniques and high-end computing resources (so-called "supercomputers"), including (i) the handling or processing large quantities of statistical information, (ii) manipulating and disseminating huge datasets, (iii) performing large numbers of calculations in parallel, (iv) the imaging and visualization of large files, and (v) large-scale or complex pattern matching and recognition.:
- Bioinformatics and computational biology: Biology has huge emerging computational needs, from data-intensive studies in genomics to computationally intensive cellular network simulations and large-scale systems modelling. Applications promise to provide revolutionary treatments of disease.
- Modelling of Enzymes and bio-molecules: The nature of the interaction of small naturally occurring molecules with large bio–macromolecules is central to most biochemical processes associated with humans. Computer aided molecular modelling is now a powerful tool to aid such drug discovery by revealing, at a molecular level, the nature of the drug–protein interaction.
- Materials science and computational nanotechnology: A key challenge in materials modelling is to provide fundamental insight into how the basic atomic structure of matter affects the function of materials. The medium/long term aim is to move towards a regime where new materials can be synthesised and processed which have desired properties, performance and environmental impact. To achieve this goal, it is necessary to develop means to model matter over a wide range of length and time-scales. At the most fundamental level of this hierarchy, first principles simulations aim to understand and predict the behaviour of electrons and atoms directly from the basic laws of quantum mechanics. Such simulations are very computationally intensive. They can lead to the discovery of materials and reactions having large economic benefits—for instance, superconductors that minimize transmission loss in power lines and reduce heating in computers.
- Catalytic processes: One of the most active recent areas of application of computational science, both because of the fundamental challenges which it poses and the wide range of key technological problems which it confronts. Modelling in catalysis comprises (i) atomistic simulation which investigates catalytic processes at the molecular level, and (ii) reaction modelling.
- Climate prediction: Many high-end computational resources in the USA and Europe and a large part of the Japanese Earth Simulator are devoted to predicting climate variations and anthropogenic climate change, so as to anticipate and be able to mitigate harmful impacts on humanity.
- Plasma physics: An important goal of plasma physics will be to produce cost-effective, clean, safe electric power from nuclear fusion. Very large simulations of the reactions in advance of building the generating devices are critical to making fusion energy feasible.
- Transportation: Whether it be an automobile, an airplane, or a spacecraft, large amounts of computational resources can be applied to understanding and improving the vehicle's airflow dynamics, fuel consumption, structure design, crashworthiness, occupant comfort, and noise reduction, all with potential economic and/or safety benefits.
- Stockpile stewardship: Several of the most powerful computers in the world are being used as part of the USA Department of Energy's Advanced Simulation and Computing (ASC) to ensure the safety and reliability of the nation's stockpile of nuclear weapons. France's CEA (Atomic Energy Commission) has a similar project.
- Intelligence/defense: Very large computing demands are made by the Department of Defense, intelligence community agencies, and related entities in order to enhance the security of the United States and its allies, including anticipating the actions of terrorists and of rogue states.
- Societal health and safety: High-end computing enables the simulation of processes and systems that affect the health and safety of our society (for instance, pollution, disaster planning, and detection of terrorist actions against local and national infrastructures), thereby facilitating government and private planning.
- Earthquakes: Supercomputing simulation of earthquakes shows promise for allowing us to predict earthquakes and to mitigate the risks associated with them.
- Geophysical exploration and geoscience: High-end computing in solid-earth geophysics involves a large amount of data handling and simulation for a range of problems in petroleum exploration, with potentially huge economic benefits. Scientific studies of plate tectonics and Earth as a geodynamo require immense supercomputing power.
- Astrophysics: High-end computer simulations are fundamental to astrophysics and play the traditional scientific role of controlled experiments in a domain where controlled experiments are extremely rare or impossible. They allow vastly accelerated time scales, so that astronomical evolution can be modelled and theories tested.
- Human/organizational systems studies: The study of macroeconomics and social dynamics is also amenable to supercomputing. For instance, the behaviour of large human populations is simulated in terms of the overall effect of decisions by hundreds of millions of individuals.
Our website contains some of the research methods involved, but these examples by no means cover the entire range of applications of these techniques.
What are the opportunities for my research?
Traditionally, advanced research computing techniques have been used primarily within the physical sciences and engineering. However, these tools are now increasingly being used across the whole spectrum of research disciplines, including the Biomedical and Life Sciences, the Social Sciences, and the Arts and Humanities.
Moreover, advanced research computing frequently stimulates groundbreaking and interdisciplinary research opportunities – examples may be found in the variety of areas listed below:
- the techniques enable research to be done which cannot be, or has not been, done in any other way, including simulations of the origin and evolution of stars and galaxies, genetic sequencing, medical and dental simulations, and visualization of large or complex scanned images;
- the techniques also enable researchers to collaborate or disseminate information in a way that would otherwise not be possible, including remote access to large research databases, inexpensive video conferencing across the Internet (Access Grid), and world-wide collaborative data analysis;
- some of the mathematical and computational techniques lend themselves particularly well to interdisciplinary research including fluid and earth mantle simulations, economic forecasting, and the modelling of molecules and proteins.
All of the above leading-edge research examples are already taking place at Cardiff University.
If you think your research may benefit from some of these techniques, or if you are interested in collaborating with researchers in related fields, please contact us - we'd be delighted to help.