Atomic Snapshots of Shared Memory

Afek, Yehunda; Attiya, Hagit; Dolev, Danny; Gafni, Eli; Merritt, Michael

doi:10.21236/ada222765

Cited by 149 publications

(359 citation statements)

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“…A system using snapshot shared memory can be implemented in a wait-free manner in terms of single-writer multi-reader read/write shared variables [1]. It follows that Theorem 5 extends to read/write systems.…”

Section: Simulation In Read/write Systemsmentioning

confidence: 93%

“…However, any system with more than one snapshot variable (even with infinitely many snapshot variables) can easily be "implemented" by a system with only a single snapshot variable, with no change in any externally-observable behavior (including behavior in the presence of failures) of the system. Likewise, a system using snapshot shared memory can be "implemented" in terms of single-writer multi-reader read/write shared variables, again with no change in externally-observable behavior; see, e.g., [1] for a construction.…”

Section: The Modelmentioning

confidence: 99%

“…A complex is a family of simplexes closed under containment. 1 For a complex K, skel k (K) denotes the subcomplex formed by all simplexes of K of size at most k + 1. For example, skel 0 (K) consists of all the vertices of K, and skel 1 (K) consists of all the vertices and all the simplexes of size two.…”

Section: Convergence Tasksmentioning

confidence: 99%

“…This makes the correctness proof more modular, and the whole presentation clearer, and is no loss of generality, since a system using snapshot shared memory can be implemented in a wait-free manner in terms of single-writer multi-reader read/write shared variables [1]. For completeness, we briefly present a version that works in read/ write shared memory systems.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The BG distributed simulation algorithm

Borowsky¹,

Gafni²,

Lynch³

et al. 2001

Distrib Comput

116

200

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We present a shared memory algorithm that allows a set of f + 1 processes to wait-free "simulate" a larger system of n processes, that may also exhibit up to f stopping failures.Applying this simulation algorithm to the k-set-agreement problem enables conversion of an arbitrary k-fault-tolerant nprocess solution for the k-set-agreement problem into a waitfree k+1-process solution for the same problem. Since the k+ 1-process k-set-agreement problem has been shown to have no wait-free solution [5,18,26], this transformation implies that there is no k-fault-tolerant solution to the n-process kset-agreement problem, for any n.More generally, the algorithm satisfies the requirements of a fault-tolerant distributed simulation. The distributed simulation implements a notion of fault-tolerant reducibility between decision problems. This paper defines these notions and gives examples of their application to fundamental distributed computing problems.The algorithm is presented and verified in terms of I/O automata. The presentation has a great deal of interesting modularity, expressed by I/O automaton composition and both forward and backward simulation relations. Composition is used to include a safe agreement module as a subroutine. Forward and backward simulation relations are used to view the algorithm as implementing a multi-try snapshot strategy.The main algorithm works in snapshot shared memory systems; a simple modification of the algorithm that works in read/write shared memory systems is also presented.

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Section: Simulation In Read/write Systemsmentioning

confidence: 93%

Section: The Modelmentioning

confidence: 99%

Section: Convergence Tasksmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The BG distributed simulation algorithm

Borowsky¹,

Gafni²,

Lynch³

et al. 2001

Distrib Comput

116

200

View full text Add to dashboard Cite

show abstract

“…We then present the first known algorithm for k-set agreement that tolerates periods of asynchrony. Our algorithm guarantees correctness, regardless of asynchrony, and terminates as soon as there is a window of synchrony of size t k + O (1). For simplicity, we show synchronous round complexity of t k + 4.…”

Section: Introductionmentioning

confidence: 97%

Of Choices, Failures and Asynchrony: The Many Faces of Set Agreement

et al. 2011

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Set agreement is a fundamental problem in distributed computing in which processes collectively choose a small subset of values from a larger set of proposals. The impossibility of fault-tolerant set agreement in asynchronous networks is one of the seminal results in distributed computing. In synchronous networks, too, the complexity of set agreement has been a significant research challenge that has now been resolved. Real systems, however, are neither purely synchronous nor purely asynchronous. Rather, they tend to alternate between periods of synchrony and periods of asynchrony. Nothing specific is known about the complexity of set agreement in such a "partially synchronous" setting.In this paper, we address this challenge, presenting the first (asymptotically) tight bound on the complexity of set agreement in such systems. We introduce a novel technique for simulating, in a fault-prone asynchronous shared memory, executions of an asynchronous and failure-prone message-passing system in which some fragments appear synchronous to some processes.We use this simulation technique to derive a lower bound on the round complexity of set agreement in a partially synchronous system by a reduction from asynchronous wait-free set agreement. Specifically, we show that every set agreement protocol requires at least t k + 2 synchronous rounds to decide. We present an (asymptotically) matching algorithm that relies on a distributed asynchrony detection mechanism to decide as soon as possible during periods of synchrony. From these two results, we derive the size of the minimal window of synchrony needed to solve set agreement.By relating synchronous, asynchronous and partially synchronous environments, our simulation technique is of independent interest. In particular, it allows us to obtain a new lower bound on the complexity of early deciding k-set agreement complementary to that of Gafni et al. (in SIAM J. Comput. 40(1):63-78, 2011), and to re-derive the combinatorial topology lower bound of : [570][571][572][573][574][575][576][577][578][579][580] 2009) in an algorithmic way.

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A liveness condition for concurrent objects: x‐wait‐freedom

Imbs¹,

Raynal²

2011

Concurrency and Computation

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The liveness of concurrent objects despite asynchrony and failures is a fundamental problem. To that end several progress conditions have been proposed. Wait-freedom is the strongest of these conditions: it states that any object operation must terminate if the invoking process does not crash. Obstructionfreedom is a weaker progress condition as it requires progress only when a process executes in isolation for a long enough period. This paper explores progress conditions in n-process asynchronous read/write systems enriched with base objects with consensus number x, 1

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Atomic Snapshots of Shared Memory

Cited by 149 publications

References 0 publications

The BG distributed simulation algorithm

The BG distributed simulation algorithm

Of Choices, Failures and Asynchrony: The Many Faces of Set Agreement

A liveness condition for concurrent objects: x‐wait‐freedom

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