Abstract
In this study we investigate the transferability of trained regression models to estimate solo run L2 cache stress of programs running on multi-core processors. We used machine learning to generate the trained regression models. Transferability of a regression model means how useful is a regression model (which is trained on one architecture) to predict the solo run L2 cache stress on another architecture. The statistical methodology to assess model transferability is discussed. We observed that regression models trained on a given L2 cache architecture are reasonably transferable to other L2 cache architecture and vice versa.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
