Massively Concurrent Red-Black Trees with Hardware Transactional Memory

Siakavaras, Dimitrios; Nikas, Konstantinos; Goumas, Georgios; Koziris, Nectarios

doi:10.1109/pdp.2016.65

Cited by 3 publications

(2 citation statements)

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“…Work done by Siakavaras et el. [33] shows that naive application of hardware transactional systems to data-structures typically perform poorly and require algorithm modifications to operate efficiently. Future work aimed at determining the optimal modifications for Robin Hood might elevate its performance for hardware transactional memory.…”

Section: Future Workmentioning

confidence: 99%

Concurrent Robin Hood Hashing

Kelly,

Pearlmutter,

Maguire

2018

Preprint

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In this paper we examine the issues involved in adding concurrency to the Robin Hood hash table algorithm. We present a non-blocking obstruction-free K-CAS Robin Hood algorithm which requires only a single word compare-and-swap primitive, thus making it highly portable. The implementation maintains the attractive properties of the original Robin Hood structure, such as a low expected probe length, capability to operate effectively under a high load factor and good cache locality, all of which are essential for high performance on modern computer architectures. We compare our data-structures to various other lock-free and concurrent algorithms, as well as a simple hardware transactional variant, and show that our implementation performs better across a number of contexts. ACM Subject Classification Theory of computation → Concurrent algorithmsKeywords and phrases concurrency, Robin Hood Hashing, data-structures, hash tables, nonblocking Funding Funded by the Government of Ireland Postgraduate Scholarship.Acknowledgements I want to thank William Leiserson for his invaluable help with reviewing and feedback. I also want to thank Nir Shavit for extensive access to hardware for running the benchmarks.

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Section: Future Workmentioning

confidence: 99%

Concurrent Robin Hood Hashing

Kelly,

Pearlmutter,

Maguire

2018

Preprint

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“…The most straightforward coarse‐grained HTM‐based ST, where each operation is enclosed in a transaction exhibits large transactions both in terms of memory footprint and duration. This approach can be easily applied to any ST, however, in today's HTM systems its large transactions lead to low performance due to the large number of capacity aborts 1,21 . Avni and Kuszmaul 22 present a fine‐grained HTM‐based tree that uses smaller transactions by excluding the search path from them.…”

Section: Introductionmentioning

confidence: 99%

RCU‐HTM: A generic synchronization technique for highly efficient concurrent search trees

Siakavaras

Nikas

Goumas

et al. 2021

Concurrency and Computation

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Concurrent search trees (STs) are among the most widely used data structures to store and retrieve data in contemporary multithreaded applications. Despite the high amount of prior work, it still remains challenging to implement highly efficient concurrent STs. This is mainly due to the fact that both traditional synchronization methods (i.e., locks and atomic operations) and more novel ones (i.e., read‐copy‐update and transactional memory) fail to provide solutions that are generic and at the same time able to attain high performance under diverse workloads and contention levels. In this work, we present RCU‐HTM, a technique that combines read‐copy‐update (RCU) and hardware transactional memory (HTM), and: (a) supports the implementation of a concurrent version of any type of search tree, and (b) achieves high performance across all execution scenarios. We also incorporate a low‐overhead, epoch‐based memory reclamation scheme to make our RCU‐HTM trees practical for large‐scale long‐running applications. To showcase the capabilities of our technique, we implement and evaluate multiple RCU‐HTM trees and compare their performance with several state‐of‐the‐art competitors. More specifically, we apply RCU‐HTM to 12 different types of binary, B+ and (a,b)‐trees and compare against 18 state‐of‐the‐art implementations that use four different synchronization mechanisms, namely, locks, atomic operations, RCU, and HTM. We evaluate the trees under different levels of contention by varying the size of the tree, the operations mix, and the number of threads, for a total of 210 execution scenarios for each implementation. Our evaluation shows that in the majority of executions, RCU‐HTM trees outperform their state‐of‐the‐art alternatives, and even in the cases where they do not, their performance is very close to that of the best implementation.

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