Dynamic-Compiler-Driven Control for Microprocessor Energy and Performance

By Qiang Wu, Margaret Martonosi, Douglas W. Clark, Vijay Janappa Reddi, D. Connors, Youfeng Wu, Jin Lee, David M. Brooks. 2006

44 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Hardware and Architecture, ML Systems & Hardware

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Young Geun Kim
2. Carole-Jean Wu
3. Udit Gupta
4. Gu-Yeon Wei
5. David M. Brooks

In Hardware and Architecture

1. Young Geun Kim
2. Gu-Yeon Wei
3. David M. Brooks
4. Carole-Jean Wu

In ML Systems & Hardware

1. Young Geun Kim
2. Carole-Jean Wu
3. Gu-Yeon Wei
4. David M. Brooks
5. Udit Gupta

Citations in the corpus

• Chasing Carbon: The Elusive Environmental Footprint of Computing (2020, background): “ramming languages. Recent work has proposed new programming languages to enable moreenergy-efficient code [94]. Others propose compiler-level optimizations to increase the code’s energy efficiency [95]–[97]. 10 Application/Algorithms Runtime systems Systems Compilers Architecture Circuits Scale down h”