Composing concurrency control

Ziv, Ofri; Aiken, Alex; Golan-Gueta, Guy; Ramalingam, G.; Sagiv, Mooly

doi:10.1145/2737924.2737970

Cited by 5 publications

(2 citation statements)

References 30 publications

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“…Among recent systems, Hekaton [6] supports pessimistic locking on top of its MVCC protocol. Ziv et al [49] formalize the theory of composing computations over multiple data structures using different CC schemes. Cao et al [3] use OCC and pessimistic CC to handle low and high conflict accesses, respectively.…”

Section: Related Workmentioning

confidence: 99%

Mostly-optimistic concurrency control for highly contended dynamic workloads on a thousand cores

Wang

Kimura

2016

Proc. VLDB Endow.

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Future servers will be equipped with thousands of CPU cores and deep memory hierarchies. Traditional concurrency control (CC) schemes-both optimistic and pessimistic-slow down orders of magnitude in such environments for highly contended workloads. Optimistic CC (OCC) scales the best for workloads with few conflicts, but suffers from clobbered reads for high conflict workloads. Although pessimistic locking can protect reads, it floods cachecoherence backbones in deep memory hierarchies and can also cause numerous deadlock aborts. This paper proposes a new CC scheme, mostly-optimistic concurrency control (MOCC), to address these problems. MOCC achieves orders of magnitude higher performance for dynamic workloads on modern servers. The key objective of MOCC is to avoid clobbered reads for high conflict workloads, without any centralized mechanisms or heavyweight interthread communication. To satisfy such needs, we devise a native, cancellable reader-writer spinlock and a serializable protocol that can acquire, release and re-acquire locks in any order without expensive interthread communication. For low conflict workloads, MOCC maintains OCC's high performance without taking read locks. Our experiments with high conflict YCSB workloads on a 288core server reveal that MOCC performs 8× and 23× faster than OCC and pessimistic locking, respectively. It achieves 17 million TPS for TPC-C and more than 110 million TPS for YCSB without conflicts, 170× faster than pessimistic methods.

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Section: Related Workmentioning

confidence: 99%

Mostly-optimistic concurrency control for highly contended dynamic workloads on a thousand cores

Wang

Kimura

2016

Proc. VLDB Endow.

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“…Quite a few authors have previously combined optimistic and pessimistic concurrency control mechanisms in the context of Database Systems. Ziv et al combined locking with Software TM (STM) in different parts of the program, obtaining better performance than just using a lock‐based or an STM‐based solution. They found that, by using one of the two choices exclusively throughout the application, execution is often sub‐optimal.…”

Section: Related Workmentioning

confidence: 99%

Power‐aware pipelining with automatic concurrency control

Torquati

Sensi

Mencagli

et al. 2018

Concurrency and Computation

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Summary Continuous streaming computations are usually composed of different modules, exchanging data through shared message queues. The selection of the algorithm used to access such queues (ie, the concurrency control) is a critical aspect both for performance and power consumption. In this paper, we describe the design of automatic concurrency control algorithm for implementing power‐efficient communications on shared‐memory multicores. The algorithm automatically switches between nonblocking and blocking concurrency protocols, getting the best from the two worlds, ie, obtaining the same throughput offered by the nonblocking implementation and the same power efficiency of the blocking concurrency protocol. We demonstrate the effectiveness of our approach using two micro‐benchmarks and two real streaming applications.

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Drinking from both glasses

Cao

Zhang

Sengupta

et al. 2016

Proceedings of the 21st ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

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It is notoriously challenging to develop parallel software systems that are both scalable and correct. Runtime support for parallelism-such as multithreaded record & replay, data race detectors, transactional memory, and enforcement of stronger memory models-helps achieve these goals, but existing commodity solutions slow programs substantially in order to track (i.e., detect or control) an execution's cross-thread dependences accurately. Prior work tracks cross-thread dependences either "pessimistically," slowing every program access, or "optimistically," allowing for lightweight instrumentation of most accesses but dramatically slowing accesses involved in cross-thread dependences. This paper seeks to hybridize pessimistic and optimistic tracking, which is challenging because there exists a fundamental mismatch between pessimistic and optimistic tracking. We address this challenge based on insights about how dependence tracking and program synchronization interact, and introduce a novel approach called hybrid tracking. Hybrid tracking is suitable for building efficient runtime support, which we demonstrate by building hybridtracking-based versions of a dependence recorder and a region serializability enforcer. An adaptive, profile-based policy makes runtime decisions about switching between pessimistic and optimistic tracking. Our evaluation shows that hybrid tracking enables runtime support to overcome the performance limitations of both pessimistic and optimistic tracking alone.

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Composing concurrency control

Cited by 5 publications

References 30 publications

Mostly-optimistic concurrency control for highly contended dynamic workloads on a thousand cores

Mostly-optimistic concurrency control for highly contended dynamic workloads on a thousand cores

Power‐aware pipelining with automatic concurrency control

Drinking from both glasses

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