Work

Enabling Practical Processing in and near Memory for Data-Intensive Computing

Year: 2019

Type: conference-paper

Abstract: Modern computing systems suffer from the dichotomy between computation on one side, which is performed only in the processor (and accelerators), and data storage/movement on the other, which all other parts of the system are dedicated to. Due to this dichotomy, data moves a lot in order for the system to perform computation on it. Unfortunately, data movement is extremely expensive in terms of energy and latency, much more so than computation. As a result, a large fraction of system energy is spent and performance is lost solely on moving data in a modern computing system.

Source: ACM/IEEE Design Automation Conference (DAC)

DOI: 10.1145/3316781.3323476

Authors: Onur Mutlu, Saugata Ghose, Juan Gómez-Luna, Rachata Ausavarungnirun

Institutions: ETH Zurich, Carnegie Mellon University

Language: English

Topic: Parallel Computing and Optimization Techniques

Subfield: Hardware and Architecture

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, Semiconductor Research Corporation, Nvidia, VMware, Eidgenössische Technische Hochschule Zürich, Samsung

OpenAlex ID: W2944576035

FWCI: 4.64

Cites: 103

Cited by: 67

Related to: 10