Estimating transaction execution times for a software transactional memory

Over the last two decades, researchers developed many software, hardware, and hybrid Transactional Memories (TMs) with various APIs and semantics. However, reduced performance when exposed to high contention loads is still the major downside of all the TMs. Although many strategies and methods have been proposed, contention management and transaction scheduling still remains an open area of research. An important piece of unsolved contention management puzzle is plausible transaction execution time estimation. In this paper we proposed two methods for estimating transaction execution times, namely the method based on log-normal distribution and the method based on gamma distribution. Experimental results presented in this paper indicate that the method based on log-normal distribution has better estimation accuracy than the method based on gamma distribution. Even more importantly, the method based on log-normal distribution uses 10 times shorter sliding windows and its complexity is much lower than for the method based on gamma distribution, thus it is faster and requires less electrical power.