Strong Scaling Key to Redrawing Neuroscience Borders

June 1, 2016 Nicole Hemsoth Computing for neuroscience, which has aided in our understanding of the structure and function of the brain, has been around for decades already. More recently, however, there has been neuroscience for computing, or the use of computational principles of the brain for generic data processing. For each of these neuroscience-driven areas there is a key limitation—scalability. This is not just scalability in terms of software or hardware systems, but on the application side, limits in terms of efficiently deploying computational tools at sufficient size and time scales to yield far greater insight. While adding more compute to the problem can push new research, there are barriers at a certain point there. And adding more neurons to a network makes the problem itself unwieldy. So what…


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