Abstract
Speculative parallelization is a runtime technique that optimistically executes sequential code in parallel, checking that no dependence violations appear. In this paper, we address the problem of minimizing the number of threads that should be restarted when a data dependence violation is found. We present a new mechanism that keeps track of inter-thread dependencies in order to selectively stop and restart offending threads, and all threads that have consumed data from them. Results show a reduction of 38.5% to 81.8% in the number of restarted threads for real application loops and up to a 10% speedup, depending on the amount of local computation.
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.
