Efficient Parallel Self-Adjusting Computation

@article{Anderson2021EfficientPS,
  title={Efficient Parallel Self-Adjusting Computation},
  author={Daniel Anderson and Guy E. Blelloch and Anubhav Baweja and Umut A. Acar},
  journal={Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures},
  year={2021}
}
Self-adjusting computation is an approach for automatically producing dynamic algorithms from static ones. It works by tracking control and data dependencies, and propagating changes through the dependencies when making an update. Extensively studied in the sequential setting, some results on parallel self-adjusting computation exist, but are only applicable to limited classes of computations, or are ad-hoc systems with no theoretical analysis of their performance. In this paper, we present the… Expand

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