Lock-free transactional vector.

PPoPP '20: 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming San Diego California February, 2020(2020)

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摘要
The vector is a fundamental data structure, offering constant-time traversal to elements and a dynamically resizable range of indices. While several concurrent vectors exist, a composition of concurrent vector operations dependent on each other can lead to undefined behavior. Techniques for providing transactional capabilities for data structure operations include Software Transactional Memory (STM) and transactional transformation methodologies. Transactional transformations convert concurrent data structures into their transactional equivalents at an operation level, rather than STM's object or memory level. To the best of our knowledge, existing STMs do not support dynamic read/write sets in a lock-free manner, and transactional transformation methodologies are unsuitable for the vector's contiguous memory layout. In this work, we present the first lock-free transactional vector. It integrates the fast lock-free resizing and instant logical status changes from related works. Our approach pre-processes transactions to reduce shared memory access and simplify access logic. This can be done without locking elements or verifying conflicts between transactions. We compare our design against state-of-the-art transactional designs, GCC STM, Transactional Boosting, and STO. All data structures are tested on four different platforms, including x86_64 and ARM architectures. We find that our lock-free transactional vector generally offers better scalability than STM and STO, and competitive performance with Transactional Boosting, but with additional lock-free guarantees. In scenarios with only reads and writes, our vector is as much as 47% faster than Transactional Boosting.
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