A PhD student at The University of Manchester has developed a new method and software for using computer game technology for complex scientific and engineering simulations.
Powerful graphics cards, also known as graphic processing units (GPUs), are usually used to create ultrafast gameplay and realistic visuals for games consoles, personal computers, and laptops. But recently, the GPU has emerged as a technology to accelerate scientific simulations, running some applications over 100 times faster than conventional computers.
Using this technology, Alex Chow, 25, from the School of Mechanical, Aerospace and Civil Engineering, is now creating largescale simulations of ‘violent fluid flows’ including powerful ocean waves crashing against offshore wind turbines to predict their potential impact forces on the structures.
Creating complex and accurate computer simulations is usually done on a so-called ‘supercomputer’. Rather than being an individual machine, a supercomputer is actually made up of hundreds of central processing units (CPUs) connected with up to thousands of computing cores. Such powerful computers are needed because these large simulations have billions of calculations and millions of data points.
These kinds of machines, although extremely powerful are very expensive, with even small clusters ranging from hundreds of thousands of pounds to millions of pounds. They also use large amounts of energy and are only accessible to a small number of researchers and scientists.
The benefit of using a graphic processing unit (GPUs) is that they’re much cheaper and energy efficient compared to usual supercomputers needed to do such complex simulations. Some GPUs are compact enough to fit in a laptop whereas supercomputers may require a whole room or dedicated facility.
“Using this kind of technology reduces the costs of complex scientific simulations from hundreds of thousands of pounds to just a couple of thousand.”
