Scalable and Performance-Critical Data Structures for Multicores

In this work, we study the scalability, performance, design and implementation of basic data structure abstractions, such as a queue, for next generation multicore systems. We propose two algorithms for concurrent queue. Our first algorithm, a wait-free queue, provides an efficient replacement to a lock-free queue. Lock-free queue is considered very efficient, but does not provide local progress guarantee for each thread. It also performs badly under stressed conditions. Our wait-free queue, not only provides local progress guarantee, but also depicts high performance and positive scalability under highly stressed conditions. Our second algorithm, a sequentially consistent queue, further achieves high performance by changing the consistency model. All the queue algroithms provide linearizability, which orders the operations on a global time scale. However, our sequentially consistent queue orders the operations in a program order, which is local to a thread. Our experimental results shows that our algorithms outperforms existing state-of-the-art algorithm by a factor of 10 to 15.