Using branch predictors to predict brain activity in brain-machine implants

Author:

Bhattacharjee Abhishek1

Affiliation:

1. Rutgers University and Princeton University

Funder

NSF

Publisher

ACM

Reference72 articles.

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3. {n. d.}. Utah array plugged. http://prometheus.med.utah.edu/bwjones/wp-content/uploads/iblog/Implant1.jpg ({n. d.}). {n. d.}. Utah array plugged. http://prometheus.med.utah.edu/bwjones/wp-content/uploads/iblog/Implant1.jpg ({n. d.}).

4. Manor Alwani Han Chen Michael Ferdman and Peter Milner. 2016. Fused-Layer CNN Accelerators. Int'l Symp. on Microarch. (2016). Manor Alwani Han Chen Michael Ferdman and Peter Milner. 2016. Fused-Layer CNN Accelerators. Int'l Symp. on Microarch. (2016).

5. Renee St. Amant Daniel Jimenez and Doug Burger. 2008. Low-Power High-Perf. Analog Neural Branch Prediction. Int'l Symp. on Microarch. (2008). 10.1109/MICRO.2008.4771812 Renee St. Amant Daniel Jimenez and Doug Burger. 2008. Low-Power High-Perf. Analog Neural Branch Prediction. Int'l Symp. on Microarch. (2008). 10.1109/MICRO.2008.4771812

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1. A survey of techniques for dynamic branch prediction;Concurrency and Computation: Practice and Experience;2018-09-02

2. Balancing the learning ability and memory demand of a perceptron-based dynamically trainable neural network;The Journal of Supercomputing;2018-04-16

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