Simple, fast, and practical non-blocking and blocking concurrent queue algorithms

Michael, Maged M.; Scott, Michael L.

doi:10.1145/248052.248106

Cited by 551 publications

(391 citation statements)

References 15 publications

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“…Elimination is less useful if the queue remains non-empty most of the time, or when concurrency is low. In contrast, CAFÉ performs well under both high and low concurrency, and regardless of the ratio between producers and consumers 7 .…”

Section: Related Workmentioning

confidence: 88%

CAFÉ: Scalable Task Pools with Adjustable Fairness and Contention

Basin

Fan

Keidar

et al. 2011

Lecture Notes in Computer Science

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Abstract. Task pools have many important applications in distributed and parallel computing. Pools are typically implemented using concurrent queues, which limits their scalability. We introduce CAFÉ, Contention and Fairness Explorer, a scalable and wait-free task pool which allows users to control the trade-off between fairness and contention. The main idea behind CAFÉ is to maintain a list of TreeContainers, a novel tree-based data structure providing efficient task inserts and retrievals. TreeContainers don't guarantee FIFO ordering on task retrievals. But by varying the size of the trees, CAFÉ can provide any type of pool, from ones using large trees with low contention but less fairness, to ones using small trees with higher contention but also greater fairness. We demonstrate the scalability of TreeContainer by proving an O(log 2 N ) bound on the step complexity of insert operations when there are N inserts, as compared to an average of Ω(N ) steps in a queue based implementation. We further prove that get operations are wait-free. Evaluations of CAFÉ show that it outperforms the Java SDK implementation of the Michael-Scott queue by a factor of 30, and is over three times faster than other state-of-the-art non-FIFO task pools.

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Section: Related Workmentioning

confidence: 88%

CAFÉ: Scalable Task Pools with Adjustable Fairness and Contention

Basin

Fan

Keidar

et al. 2011

Lecture Notes in Computer Science

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“…For the MPMC case we used the lock-free queue by Michael and Scott, henceforth called the MS-Queue [7]. It is based on a linked-list and adds items to the queue by using CAS to swap in a pointer at the tail node.…”

Section: Mpmc Queuesmentioning

confidence: 99%

“…To compare lock-free synchronization with blocking, we used the lock-based queue by Michael and Scott, which stores elements in a linked-list [7]. We used both the standard version, with separate locks for the enqueue and dequeue operation, and a simpler version with a common lock for both operations.…”

Section: Mpmc Queuesmentioning

confidence: 99%

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Understanding the Performance of Concurrent Data Structures on Graphics Processors

Cederman

Chatterjee

Tsigas

2012

Euro-Par 2012 Parallel Processing

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Abstract. In this paper we revisit the design of concurrent data structures -specifically queues -and examine their performance portability with regard to the move from conventional CPUs to graphics processors. We have looked at both lock-based and lock-free algorithms and have, for comparison, implemented and optimized the same algorithms on both graphics processors and multi-core CPUs. Particular interest has been paid to study the difference between the old Tesla and the new Fermi and Kepler architectures in this context. We provide a comprehensive evaluation and analysis of our implementations on all examined platforms. Our results indicate that the queues are in general performance portable, but that platform specific optimizations are possible to increase performance. The Fermi and Kepler GPUs, with optimized atomic operations, are observed to provide excellent scalability for both lock-based and lock-free queues.

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“…We implemented several nonblocking algorithms using TxAtomicRef including Michael and Scott's lock-free queue [4] and Harris' lock-free linked list [1] (results in Figure 1). In all cases we simply replaced the AtomicReferences in the original algorithms with TxAtomicRefs in our constructions.…”

mentioning

confidence: 99%

Transaction Safe Nonblocking Data Structures

Marathe

Spear

Scott

Lecture Notes in Computer Science

Self Cite

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This brief announcement focuses on interoperability of software transactions with ad hoc nonblocking algorithms. Specifically, we modify arbitrary nonblocking operations so that (1) they can be used both inside and outside transactions, (2) external uses serialize with transactions, and (3) internal uses succeed if and only if the surrounding transaction commits. Interoperability enables seemless integration with legacy code, atomic composition of nonblocking operations, and the equivalent of hand-optimized, closed nested transactions.The key to transaction safety is to ensure that memory accesses of operations called from inside a transaction occur (or appear to occur) if, only if, and when the surrounding transaction commits. We do this by making writes manifestly speculative, with their fate tied to that of the transaction, and by logging reads for re-validation immediately before the transaction commits. (Because correct nonblocking code is designed to tolerate races, additional, intermediate validation is not required.) When called from outside a transaction, operations behave as they did in the original nonblocking code, except that they aggressively abort any transaction that stands in their way. Operations inside a transaction similarly abort transactional peers. They are unaware of nontransactional peers.We provide nonblocking objects with "transaction aware" versions of references and other basic primitive types such as integer, long, etc. These provide Get, Set, and CAS operations, which the programmer uses instead of conventional accesses. If called inside a transaction, Get logs the target location for later validation; Set and CAS speculatively modify the target location. Changes become permanent at transaction commit time. If called outside a transaction, all three operations "clean up" any encountered speculative updates, aborting conflicting transactions if necessary. Given correct nonblocking code, the changes required to create a transaction-safe version are mechanical.To make a type transaction-aware, we must be able to distinguish between real and speculative values. For some types (e.g., pointers in C) we may be able to claim an otherwise unused bit, or use features such as runtime type identification in strongly typed languages such as Java. For others we may use a sentinel value to trigger address-based lookup in a separate metadata table.With support for transaction aware primitives, we expect that construction of transaction safe versions of nonblocking algorithms would require little or no ⋆

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Simple, fast, and practical non-blocking and blocking concurrent queue algorithms

Cited by 551 publications

References 15 publications

CAFÉ: Scalable Task Pools with Adjustable Fairness and Contention

CAFÉ: Scalable Task Pools with Adjustable Fairness and Contention

Understanding the Performance of Concurrent Data Structures on Graphics Processors

Transaction Safe Nonblocking Data Structures

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