Integrating Transactionally Boosted Data Structures with STM Frameworks: A Case Study on Set

Providing transactional collections of data structures with the same performance of highly concurrent data structures enables performance-competitive transactional composability. Although Software Transactional Memory (STM) is increasingly becoming a promising technology for designing and implementing transactional applications, concurrent data structures still do not exploit STM’s advantages. Recently, Optimistic Transactional Boosting (OTB) has been proposed as a methodology to implement transactional versions of highly concurrent data structures. OTB works in a similar way to STM algorithms, but on the level of data structure semantics. This similarity is a motivation for finding a way to integrate operations of transactional data structures with STM frameworks. In this paper, we extend the design of DEUCE, a Java STM framework, to support OTB integration. Using our extension, programmers can include both OTB data structure operations and traditional memory reads/writes in the same transaction, and the framework will guarantee that both will execute safely as an atomic block. While keeping the same simple interface and the same independence from the JVM as the original DEUCE framework, we allow developers to easily integrate more OTB data structures. As a case study, we show the implementation details of OTB-Set, a transactionally boosted linked-list-based set, and we show how different STM algorithms like NOrec and TL2 can interact with it. Our experiments show up to 10x improvement in the performance of micro-benchmarks over the original DEUCE framework.