In a bid to improve understanding of neurological disorders, researchers have created a fast and energy-efficient simulation of part of a rat brain by using computer chip manufacturer Nvidia’s Artificial Intelligence (AI) compute platform.
Developing faster and more efficient simulators could increase the level of understanding the brain function and identify how damage to a particular structure in neurons can lead to deficits in brain function.
For creating the simulator, the researchers used computer hardware designed for 3D games, according to the study published in the journal Frontiers in Neuroscience.
The study showed that a single Graphics Processing Unit (GPU) was able to achieve processing speeds up to 10 per cent faster than is currently possible using either a supercomputer or the SpiNNaker neuromorphic system, a custom-built machine.
The team was also able to achieve energy savings of 10 times compared to either the SpiNNaker or supercomputer simulations.
The academics hope that the flexibility and power of GPUs means that they could play a key role in creating simulators capable of running models that begin to approach the complexity of the human brain.
“Our work shows that, in the near term, they (GPUs) are a competitive design for high performance computing and have the potential to make advances far beyond where CPUs have brought us to so far,” said Thomas Nowotny Professor of Informatics at the University of Sussex in Britain.
“We are very impressed by the use of the Nvidia AI compute platform for brain simulations spear-headed at the University of Sussex and are glad we are able to support research at the leading edge of computational neuroscience as well as AI,” Chris Emerson, Head of Higher-Education and Research Sales in UK and Ireland at Nvidia, said in a statement.