Loading…
Automatic Tuning of Compilers Using Machine Learning
This book explores break-through approaches to tackling and mitigating the well-known problems of compiler optimization using design space exploration and machine learning techniques. It demonstrates that not all the optimization passes are suitable for use within an optimization sequence and that,...
Main Authors: | Ashouri, Amir H. (Author), Palermo, Gianluca (Author), Cavazos, John (Author), Silvano, Cristina (Author) |
---|---|
Corporate Author: | SpringerLink (Online service) |
Format: | e-Book |
Language: | English |
Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2018.
|
Edition: | 1st ed. 2018. |
Series: | PoliMI SpringerBriefs,
|
Subjects: | |
Online Access: | Full-text access View in OPAC |
Similar Items
-
Separation Logic for High-level Synthesis
by: Winterstein, Felix
Published: (2017) -
Advanced Finite Element Simulation with MSC Marc Application of User Subroutines /
by: Javanbakht, Zia, et al.
Published: (2017) -
Speech and Language Processing for Human-Machine Communications Proceedings of CSI 2015 /
Published: (2018) -
Advances in Neural Computation, Machine Learning, and Cognitive Research Selected Papers from the XIX International Conference on Neuroinformatics, October 2-6, 2017, Moscow, Russia /
Published: (2018) -
Machine Learning for Evolution Strategies
by: Kramer, Oliver
Published: (2016)