Indranil R. Bardhan, Sugato Bagchi, et al.
JMIS
This paper describes the implementation of an online feedback-directed optimization system. The system is fully automatic; it requires no prior (offline) profiling run. It uses a previously developed low-overhead instrumentation sampling framework to collect control flow graph edge profiles. This profile information is used to drive several traditional optimizations, as well as a novel algorithm for performing feedback-directed control flow graph node splitting. We empirically evaluate this system and demonstrate improvements in peak performance of up to 17% while keeping overhead low, with no individual execution being degraded by more than 2% because of instrumentation.
Indranil R. Bardhan, Sugato Bagchi, et al.
JMIS
Renu Tewari, Richard P. King, et al.
IS&T/SPIE Electronic Imaging 1996
Israel Cidon, Leonidas Georgiadis, et al.
IEEE/ACM Transactions on Networking
Rajiv Ramaswami, Kumar N. Sivarajan
IEEE/ACM Transactions on Networking