Title
MLComp: A Methodology for Machine Learning-based Performance Estimation and Adaptive Selection of Pareto-Optimal Compiler Optimization Sequences
Abstract
Embedded systems have proliferated in various consumer and industrial applications with the evolution of Cyber-Physical Systems and the Internet of Things. These systems are subjected to stringent constraints so that embedded software must be optimized for multiple objectives simultaneously, namely reduced energy consumption, execution time, and code size. Compilers offer optimization phases to im...
Year
DOI
Venue
2021
10.23919/DATE51398.2021.9474158
2021 Design, Automation & Test in Europe Conference & Exhibition (DATE)
Keywords
DocType
ISBN
Measurement,Training,Adaptation models,Analytical models,Energy consumption,Sequential analysis,Estimation
Conference
978-3-9819263-5-4
Citations 
PageRank 
References 
0
0.34
0
Authors
9
Name
Order
Citations
PageRank
Alessio Colucci132.40
Dávid Juhász200.34
Martin Mosbeck300.34
Alberto Marchisio4328.58
Semeen Rehman544731.92
Manfred Kreutzer600.34
Guenther Nadbath700.34
Axel Jantsch81875169.83
Muhammad Shafique91945157.67