Computer Systems for Neuroscience

Seminar
Tuesday, November 28, 2017
3:30 PM to 4:30 PM
POB 2.402
Free and open to the public

Computer systems are vital to advancing our understanding of the brain. From embedded chips in brain implants, to server systems used for large-scale brain modeling frameworks, computer systems help shed light on the link between low-level neuronal activity and the brain's behavioral and cognitive operation. This talk will show the challenges facing such computer systems. We will discuss the extreme energy needs of hardware used in brain implants, and the challenges posed by the computational and data requirements of large-scale brain modeling software. To address these problems, we will discuss recent results from my lab on augmenting hardware to operate harmoniously with software and even the underlying biology of these systems. For example, we will show that perceptron-based hardware branch predictors can be co-opted to predict neuronal spiking activity and can guide power management on brain implants. Further, we will show that the virtual memory layer is a performance bottleneck in server systems for brain modeling software, but that intelligent coordination with the OS layer can counteract many of the memory management problems faced by these systems. Overall, this talk offers techniques that can continue to aid the development of neuroscientific tools.

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Speaker

Bhattacharjee

Abhishek Bhattacharjee

Associate Professor
Rutgers University

Abhishek Bhattacharjee is an Associate Professor of Computer Science at Rutgers University. His is also a 2017 CV Starr Fellow at the Princeton Neuroscience Institute. His research interests are at the hardware/software interface. Some of the research results from his lab are in widespread commercial use and are implemented in AMD's latest line of processors and the Linux OS. Abhishek is a recipient of the NSF's CAREER award, research awards from Google and VMware, and the Chancellor's Award for Faculty Excellence in Research at Rutgers.