Work

Using Approximate DRAM for Enabling Energy-Efficient, High-Performance Deep Neural Network Inference

Year: 2023

Type: book-chapter

Source: Springer eBooks

DOI: 10.1007/978-3-031-19568-6_10

Authors: Lois Orosa, Skanda Koppula, Konstantinos Kanellopoulos, A. Giray Yağlıkçı, Onur Mutlu

Institutions: Centro de Supercomputación de Galicia, ETH Zurich, Google DeepMind (United Kingdom), Google (United Kingdom)

Language: English

Topic: Low-power high-performance VLSI design

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: closed

OpenAlex ID: W4387219884

FWCI: 1.72

Cites: 71

Cited by: 2

Related to: 10