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ISAAC: A Convolutional Neural Network Accelerator with In ...

October 5th 2016: This version corrects some of the results for the ISAAC-PE and ISAAC-SE configurations. ISAAC: A Convolutional Neural Network Accelerator with In-Situ Analog Arithmetic in Crossbars Ali Shafiee , Anirban Nag , Naveen Muralimanohar , Rajeev Balasubramonian , John Paul Strachan , Miao Hu , R. Stanley Williams , Vivek Srikumar . School of Computing, University of Utah, Salt Lake City, Utah, USA. Email: {shafiee, anirban, rajeev, Hewlett Packard Labs, Palo Alto, California, USA. Email: { , , , Abstract with an approach rooted in near data processing. A DaDi- A number of recent efforts have attempted to design accel- anNao system employs a number of connected chips (nodes), erators for popular machine learning algorithms, such as those each made up of 16 tiles.}}

example of in-situ computing [2], [30], [53]. While DaDian-Nao executes multiple layers and multiple neurons on a single NFU with time multiplexing, a crossbar can’t be efficiently re-programmed on the fly. Therefore, a crossbar is dedicated to process a set of neurons in a given CNN layer. The outputs

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