Non-blocking Patricia Tries with Replace Operations

Shafiei, Niloufar

doi:10.1109/icdcs.2013.43

Cited by 25 publications

(4 citation statements)

References 22 publications

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“…It uses the cooperative technique that was originated by Turek, Shasha and Prakash [18] and Barnes [2]. Subsequently, this general approach was also used to implement k-ary search trees [5], node-oriented BSTs [9], and Patricia tries [14]. Recently, Brown, Ellen and Ruppert [4] generalized this approach by providing a template for implementing updates to any data structure based on a downtree.…”

Section: Related Workmentioning

confidence: 99%

“…However, they did not provide a bound on the complexity of their implementation. In the subsequent four years, there have been many novel non-blocking implementations of various types of search trees [3,4,5,9,11,12,14,15]. Like [7], none have complexity analyses; instead, researchers have relied on experiments to evaluate and compare the performance of the search tree implementations.…”

Section: Introductionmentioning

confidence: 98%

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The amortized complexity of non-blocking binary search trees

Ellen

Fatourou

Helga

et al. 2014

Proceedings of the 2014 ACM Symposium on Principles of Distributed Computing

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We improve upon an existing non-blocking implementation of a binary search tree from single-word compare-and-swap instructions. We show that the worst-case amortized step complexity of performing a Find, Insert or Delete operation op on the tree is O(h(op) +ċ(op)) where h(op) is the height of the tree at the beginning of op andċ(op) is the maximum number of operations accessing the tree at any one time during op. This is the first bound on the complexity of a non-blocking implementation of a search tree.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

The amortized complexity of non-blocking binary search trees

Ellen

Fatourou

Helga

et al. 2014

Proceedings of the 2014 ACM Symposium on Principles of Distributed Computing

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“…It is commonly seen in nonblocking algorithms [9,29,39,41] that operations first attempt to change several locations from a clean state to some intermediate state, and then restore them back to a clean state. Given that an update is performed within a transaction, and all stores to a location appear atomically, the temporary change to intermediate states can be eliminated.…”

Section: Optimizing Prefix Transactionsmentioning

confidence: 99%

Transactional Acceleration of Concurrent Data Structures

Liu

Zhou

Spear

2015

Proceedings of the 27th ACM Symposium on Parallelism in Algorithms and Architectures

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Concurrent data structures are a fundamental building block for scalable multi-threaded programs. While Transactional Memory (TM) was originally conceived as a mechanism for simplifying the creation of concurrent data structures, modern hardware TM systems lack the progress properties needed to completely obviate traditional techniques for designing concurrent data structures, especially those requiring nonblocking progress guarantees.In this paper, we introduce the Prefix Transaction Optimization (PTO) technique for employing hardware TM to accelerate existing concurrent data structures. Our technique consists of three stages: the creation of a prefix transaction, the mechanical optimization of the prefix transaction, and then algorithm-specific optimizations to further improve performance. We apply PTO to five nonblocking data structures, and observe speedups of up to 1.5x at one thread, and up to 3x at 8 threads.

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“…Ellen et al [15] gave a provably correct, non-blocking implementation of leaf-oriented BSTs directly from single-word CAS. A similar approach was used for k-ary search trees [11] and Patricia tries [28]. All three used the cooperative technique originated by Turek, Shasha and Prakash [31] and Barnes [4].…”

Section: Related Workmentioning

confidence: 99%

A general technique for non-blocking trees

2014

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Abstract. We describe a general technique for obtaining provably correct, non-blocking implementations of a large class of tree data structures where pointers are directed from parents to children. Updates are permitted to modify any contiguous portion of the tree atomically. Our non-blocking algorithms make use of the LLX, SCX and VLX primitives, which are multi-word generalizations of the standard LL, SC and VL primitives and have been implemented from single-word CAS [10]. To illustrate our technique, we describe how it can be used in a fairly straightforward way to obtain a non-blocking implementation of a chromatic tree, which is a relaxed variant of a red-black tree. The height of the tree at any time is O(c + log n), where n is the number of keys and c is the number of updates in progress. We provide an experimental performance analysis which demonstrates that our Java implementation of a chromatic tree rivals, and often significantly outperforms, other leading concurrent dictionaries.

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Non-blocking Patricia Tries with Replace Operations

Cited by 25 publications

References 22 publications

The amortized complexity of non-blocking binary search trees

The amortized complexity of non-blocking binary search trees

Transactional Acceleration of Concurrent Data Structures

A general technique for non-blocking trees

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