Work

Efficient neural network acceleration on GPGPU using content addressable memory

Year: 2017

Type: conference-paper

Source: Design, Automation, and Test in Europe

DOI: 10.23919/date.2017.7927141

Authors: Mohsen Imani, Daniel Peroni, Yeseong Kim, Abbas Rahimi, Tajana Rosing

Institutions: University of California San Diego, University of California, Berkeley

Language: English

Topic: Parallel Computing and Optimization Techniques

Subfield: Hardware and Architecture

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

Funders: National Science Foundation, Jacobs School of Engineering, University of California, San Diego

OpenAlex ID: W2587527900

FWCI: 6.009

Cites: 33

Cited by: 48

Related to: 10