Rcu-Htm: A Generic Synchronization Technique For Highly Efficient Concurrent Search Trees

Concurrent search trees (STs) are among the most widely used data structures to store and retrieve data in contemporary multithreaded applications. Despite the high amount of prior work, it still remains challenging to implement highly efficient concurrent STs. This is mainly due to the fact that both traditional synchronization methods (i.e., locks and atomic operations) and more novel ones (i.e., read-copy-update and transactional memory) fail to provide solutions that are generic and at the same time able to attain high performance under diverse workloads and contention levels. In this work, we present RCU-HTM, a technique that combines read-copy-update (RCU) and hardware transactional memory (HTM), and: (a) supports the implementation of a concurrent version of any type of search tree, and (b) achieves high performance across all execution scenarios. We also incorporate a low-overhead, epoch-based memory reclamation scheme to make our RCU-HTM trees practical for large-scale long-running applications. To showcase the capabilities of our technique, we implement and evaluate multiple RCU-HTM trees and compare their performance with several state-of-the-art competitors. More specifically, we apply RCU-HTM to 12 different types of binary, B+ and (a,b)-trees and compare against 18 state-of-the-art implementations that use four different synchronization mechanisms, namely, locks, atomic operations, RCU, and HTM. We evaluate the trees under different levels of contention by varying the size of the tree, the operations mix, and the number of threads, for a total of 210 execution scenarios for each implementation. Our evaluation shows that in the majority of executions, RCU-HTM trees outperform their state-of-the-art alternatives, and even in the cases where they do not, their performance is very close to that of the best implementation.