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Parallel Finger Search Structures

Authors Seth Gilbert, Wei Quan Lim

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LIPIcs.DISC.2019.20.pdf
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Author Details

Seth Gilbert
  • Computer Science, National University of Singapore
Wei Quan Lim
  • Computer Science, National University of Singapore

Funding

This research was supported in part by Singapore MOE AcRF Tier 1 grant T1 251RES1719.

Acknowledgements

We would like to express our gratitude to our families and friends for their wholehearted support, to the kind reviewers who provided helpful feedback, and to all others who have given us valuable comments and advice.

Cite AsGet BibTex

Seth Gilbert and Wei Quan Lim. Parallel Finger Search Structures. In 33rd International Symposium on Distributed Computing (DISC 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 146, pp. 20:1-20:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/LIPIcs.DISC.2019.20

Abstract

In this paper we present two versions of a parallel finger structure FS on p processors that supports searches, insertions and deletions, and has a finger at each end. This is to our knowledge the first implementation of a parallel search structure that is work-optimal with respect to the finger bound and yet has very good parallelism (within a factor of O(log p)^2) of optimal). We utilize an extended implicit batching framework that transparently facilitates the use of FS by any parallel program P that is modelled by a dynamically generated DAG D where each node is either a unit-time instruction or a call to FS. The work done by FS is bounded by the finger bound F_L (for some linearization L of D), i.e. each operation on an item with distance r from a finger takes O(log r+1) amortized work. Running P using the simpler version takes O((T_1+F_L)/p + T_infty + d * ((log p)^2 + log n)) time on a greedy scheduler, where T_1, T_infty are the size and span of D respectively, and n is the maximum number of items in FS, and d is the maximum number of calls to FS along any path in D. Using the faster version, this is reduced to O((T_1+F_L)/p + T_infty + d *(log p)^2 + s_L) time, where s_L is the weighted span of D where each call to FS is weighted by its cost according to F_L. FS can be extended to a fixed number of movable fingers. The data structures in our paper fit into the dynamic multithreading paradigm, and their performance bounds are directly composable with other data structures given in the same paradigm. Also, the results can be translated to practical implementations using work-stealing schedulers.

Subject Classification

ACM Subject Classification
  • Theory of computation → Parallel algorithms
  • Theory of computation → Shared memory algorithms
  • Theory of computation → Parallel computing models
Keywords
  • Parallel data structures
  • Multithreading
  • Dictionaries
  • Comparison-based Search
  • Distribution-sensitive algorithms

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