Concurrent Treaps and Impact of Locking Objects

We propose algorithms to perform operations concurrently on treaps in a shared memory multi-core environment. Concurrent treaps hold the advantage of using nodes’ priority for maintaining the height of the treaps. To achieve synchronization, concurrent treaps make use of fine-grained locking mechani...

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Veröffentlicht in:	New generation computing Jg. 38; H. 1; S. 187 - 212
Hauptverfasser:	Alapati, Praveen, Mutyam, Madhu, Saranam, Swamy
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Tokyo Ohmsha 01.03.2020 Springer Nature B.V
Schlagworte:	Algorithms Artificial Intelligence Computer Hardware Computer Science Computer Systems Organization and Communication Networks Data structures Locking Nodes Software Engineering/Programming and Operating Systems Synchronism Trees Treaps Concurrent data structures Locking objects Concurrency
ISSN:	0288-3635, 1882-7055
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Abstract	We propose algorithms to perform operations concurrently on treaps in a shared memory multi-core environment. Concurrent treaps hold the advantage of using nodes’ priority for maintaining the height of the treaps. To achieve synchronization, concurrent treaps make use of fine-grained locking mechanism along with logical ordering and physical ordering of nodes’ keys. We initially study the throughput and performance-per-Watt (PPW) of our concurrent treap implementation and observe that it scales well, and performs better than the state-of-the-art implementations. We further continue studies to understand the impact of different locking objects on both throughput and PPW. Our experiments show that a concurrent treap implementation that uses AtomicInteger as the locking object provides better throughput and PPW, at the same time uses a low memory footprint. As part of the application study, we consider concurrent interval trees by choosing different underlying concurrent search tree implementations as the base. We observe that the concurrent interval tree implementation that uses concurrent treap as an underlying data structure provides better throughput.
AbstractList	We propose algorithms to perform operations concurrently on treaps in a shared memory multi-core environment. Concurrent treaps hold the advantage of using nodes’ priority for maintaining the height of the treaps. To achieve synchronization, concurrent treaps make use of fine-grained locking mechanism along with logical ordering and physical ordering of nodes’ keys. We initially study the throughput and performance-per-Watt (PPW) of our concurrent treap implementation and observe that it scales well, and performs better than the state-of-the-art implementations. We further continue studies to understand the impact of different locking objects on both throughput and PPW. Our experiments show that a concurrent treap implementation that uses AtomicInteger as the locking object provides better throughput and PPW, at the same time uses a low memory footprint. As part of the application study, we consider concurrent interval trees by choosing different underlying concurrent search tree implementations as the base. We observe that the concurrent interval tree implementation that uses concurrent treap as an underlying data structure provides better throughput. We propose algorithms to perform operations concurrently on treaps in a shared memory multi-core environment. Concurrent treaps hold the advantage of using nodes’ priority for maintaining the height of the treaps. To achieve synchronization, concurrent treaps make use of fine-grained locking mechanism along with logical ordering and physical ordering of nodes’ keys. We initially study the throughput and performance-per-Watt (PPW) of our concurrent treap implementation and observe that it scales well, and performs better than the state-of-the-art implementations. We further continue studies to understand the impact of different locking objects on both throughput and PPW. Our experiments show that a concurrent treap implementation that uses AtomicInteger as the locking object provides better throughput and PPW, at the same time uses a low memory footprint. As part of the application study, we consider concurrent interval trees by choosing different underlying concurrent search tree implementations as the base. We observe that the concurrent interval tree implementation that uses concurrent treap as an underlying data structure provides better throughput.
Author	Saranam, Swamy Mutyam, Madhu Alapati, Praveen
Author_xml	– sequence: 1 givenname: Praveen orcidid: 0000-0002-6746-3136 surname: Alapati fullname: Alapati, Praveen email: praveena@cse.iitm.ac.in organization: Department of Computer Science and Engineering, Indian Institute of Technology Madras – sequence: 2 givenname: Madhu surname: Mutyam fullname: Mutyam, Madhu organization: Department of Computer Science and Engineering, Indian Institute of Technology Madras – sequence: 3 givenname: Swamy surname: Saranam fullname: Saranam, Swamy organization: Department of Computer Science and Engineering, Indian Institute of Technology Madras
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Cites_doi	10.1145/274787.274812 10.1145/78969.78972 10.1007/BF01940876 10.1007/978-3-319-65482-9_63 10.1145/78973.78977 10.1145/1897852.1897873 10.1145/2692916.2555256 10.1109/SFCS.1989.63531 10.1007/978-3-642-40047-6_25 10.1145/1840845.1840883 10.1145/2692916.2555269 10.1145/1837853.1693488 10.1145/1835698.1835736
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SubjectTerms	Algorithms Artificial Intelligence Computer Hardware Computer Science Computer Systems Organization and Communication Networks Data structures Locking Nodes Software Engineering/Programming and Operating Systems Synchronism
Title	Concurrent Treaps and Impact of Locking Objects
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