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Computer Hardware for 3D Games Could Hold the Key to Replicating the Brain


James Knight (left) and Thomas Nowotny beat a top 50 supercomputer by running brain simulations using their own GeNN software and graphics processing units.

University of Sussex researchers have developed what they describe as the fastest, most energy-efficient simulation of part of a rat brain, using off-the-shelf computer hardware.

Credit: University of Sussex.

Researchers at the University of Sussex in the U.K. have developed what they describe as the fastest, most energy-efficient simulation of part of a rat brain, using off-the-shelf computer hardware.

The researchers' model beat a top 50 supercomputer by running brain simulations using their GeNN (GPU-enhanced Neuronal Networks) software and graphics processing units (GPUs).

The researchers’ goals were to increase understanding into brain function, and to identify how damage to particular structures in neurons can lead to deficits in brain function.

The researchers used the GeNN software to implement and test two established computational neuroscience models: one of a cortical microcircuit consisting of eight populations of neurons, and a balanced random network with spike-timing dependent plasticity.

The team achieved energy savings of 10 times compared to either the SpiNNaker or supercomputer simulations.

From University of Sussex (U.K.)
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