Optimizing Linearizable Bulk Operations on Data Structures.

ICPP '20: Proceedings of the 49th International Conference on Parallel Processing(2020)

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摘要
We study the problem of ensuring the correctness of concurrent programs that perform mutating foreach and range operations over concurrent data structures. We introduce three algorithms which vary in the location and the granularity of concurrency control metadata. Our algorithms make the linearization of bulk operations visible to concurrent elemental operations, which enables them to scale well, keep overhead low, and operate within tight memory bounds. In our experimental evaluation, we demonstrate that our techniques do not hinder the performance of elemental operations in elemental-only workloads, and allow scalability among concurrent mutating bulk operations. Furthermore, in mixed workloads, our algorithms outperform the baseline, sometimes by an order of magnitude or more.
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