Improving efficacy of internal binary search trees using local recovery
Article No.: 42, Pages 1 - 2
Abstract
Binary Search Tree (BST) is an important data structure for managing ordered data. Many algorithms---blocking as well as non-blocking---have been proposed for concurrent manipulation of a binary search tree in an asynchronous shared memory system that supports search, insert and delete operations based on both external and internal representations of a search tree.
An important step in executing an operation on a tree is to traverse the tree from top-to-down in order to locate the operation's window. A process may need to perform this traversal several times to handle any failures occurring due to other processes performing conflicting actions on the tree. Most concurrent algorithms that have proposed so far use a naïve approach and simply restart the traversal from the root of the tree.
In this work, we present a new approach to recover from such failures more efficiently in a concurrent binary search tree based on internal representation using local recovery by restarting the traversal from the "middle" of the tree in order to locate an operation's window. Our approach is sufficiently general in the sense that it can be applied to a variety of concurrent binary search trees based on both blocking and non-blocking approaches.
Using experimental evaluation, we demonstrate that our local recovery approach can yield significant speed-ups of up to 69% for many concurrent algorithms.
References
[1]
M. Arbel and H. Attiya. Concurrent Updates with RCU: Search Tree as an Example. In Proceedings of the 33rd ACM Symposium on Principles of Distributed Computing (PODC), pages 196--205, July 2014.
[2]
D. Drachsler, M. Vechev, and E. Yahav. Practical Concurrent Binary Search Trees via Logical Ordering. In Proceedings of the 19th ACM Symposium on Principles and Practice of Parallel Programming (PPoPP), pages 343--356, Feb. 2014.
[3]
S. V. Howley and J. Jones. A Non-Blocking Internal Binary Search Tree. In Proceedings of the 24th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), pages 161--171, June 2012.
[4]
A. Ramachandran and N. Mittal. CASTLE: Fast Concurrent Internal Binary Search Tree using Edge-Based Locking. In Proceedings of the 20th ACM Symposium on Principles and Practice of Parallel Programming (PPoPP), pages 281--282, Feb. 2015.
[5]
A. Ramachandran and N. Mittal. Improving Efficacy of Internal Binary Search Trees using Local Recovery. Technical Report UTDCS-13-15, Department of Computer Science, The University of Texas at Dallas, Dec. 2015.
Index Terms
- Improving efficacy of internal binary search trees using local recovery
Recommendations
Fast concurrent lock-free binary search trees
PPoPP '14: Proceedings of the 19th ACM SIGPLAN symposium on Principles and practice of parallel programmingWe present a new lock-free algorithm for concurrent manipulation of a binary search tree in an asynchronous shared memory system that supports search, insert and delete operations. In addition to read and write instructions, our algorithm uses (single-...
CASTLE: fast concurrent internal binary search tree using edge-based locking
PPoPP 2015: Proceedings of the 20th ACM SIGPLAN Symposium on Principles and Practice of Parallel ProgrammingWe present a new lock-based algorithm for concurrent manipulation of a binary search tree in an asynchronous shared memory system that supports search, insert and delete operations. Some of the desirable characteristics of our algorithm are: (i) a ...
Improving efficacy of concurrent internal binary search trees using local recovery
ICDCN '19: Proceedings of the 20th International Conference on Distributed Computing and NetworkingBinary Search Tree (BST) is an important data structure for managing ordered data. Many algorithms have been proposed for concurrent manipulation of a binary search tree in an asynchronous shared memory system that supports search, insert and delete ...
Comments
Information & Contributors
Information
Published In
August 2016
405 pages
February 2016420 pages
Copyright © 2016 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 27 February 2016
Published in SIGPLAN Volume 51, Issue 8
Check for updates
Author Tags
Qualifiers
- Research-article
Funding Sources
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- View Citations3Total Citations
- 612Total Downloads
- Downloads (Last 12 months)68
- Downloads (Last 6 weeks)15
Reflects downloads up to 10 Aug 2024
Other Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in