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54
WaitFree Synchronization
 ACM Transactions on Programming Languages and Systems
, 1993
"... A waitfree implementation of a concurrent data object is one that guarantees that any process can complete any operation in a finite number of steps, regardless of the execution speeds of the other processes. The problem of constructing a waitfree implementation of one data object from another lie ..."
Abstract

Cited by 732 (27 self)
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A waitfree implementation of a concurrent data object is one that guarantees that any process can complete any operation in a finite number of steps, regardless of the execution speeds of the other processes. The problem of constructing a waitfree implementation of one data object from another lies at the heart of much recent work in concurrent algorithms, concurrent data structures, and multiprocessor architectures. In the first part of this paper, we introduce a simple and general technique, based on reduction to a consensus protocol, for proving statements of the form "there is no waitfree implementation of X by Y ." We derive a hierarchy of objects such that no object at one level has a waitfree implementation in terms of objects at lower levels. In particular, we show that atomic read/write registers, which have been the focus of much recent attention, are at the bottom of the hierarchy: they cannot be used to construct waitfree implementations of many simple and familiar da...
A methodology for implementing highly concurrent data structures
 In 2nd Symp. Principles & Practice of Parallel Programming
, 1990
"... A con.curren.t object is a data structure shared by concurrent processes. Conventional techniques for implementing concurrent objects typically rely on criticaI sections: ensuring that only one process at a time can operate on the object. Nevertheless, critical sections are poorly suited for asynchr ..."
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Cited by 320 (12 self)
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A con.curren.t object is a data structure shared by concurrent processes. Conventional techniques for implementing concurrent objects typically rely on criticaI sections: ensuring that only one process at a time can operate on the object. Nevertheless, critical sections are poorly suited for asynchronous systems: if one process is halted or delayed in a critical section, other, nonfaulty processes will be unable to progress. By contrast, a concurrent object implementation is nonblocking if it always guarantees that some process will complete an operation in a finite number of steps, and it is waitfree if it guarantees that each process will complete an operation in a finite number of steps. This paper proposes a new methodology for constructing nonblocking aud waitfree implementations of concurrent objects. The objectâ€™s representation and operations are written as st,ylized sequential programs, with no explicit synchronization. Each sequential operation is automatically transformed into a nonblocking or waitfree operation usiug novel synchronization and memory management algorithms. These algorithms are presented for a multiple instruction/multiple data (MIM D) architecture in which n processes communicate by applying read, write, and comparekYswa,p operations to a shared memory. 1
Fast Randomized Consensus using Shared Memory
 Journal of Algorithms
, 1988
"... We give a new randomized algorithm for achieving consensus among asynchronous processes that communicate by reading and writing shared registers. The fastest previously known algorithm has exponential expected running time. Our algorithm is polynomial, requiring an expected O(n 4 ) operations ..."
Abstract

Cited by 130 (32 self)
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We give a new randomized algorithm for achieving consensus among asynchronous processes that communicate by reading and writing shared registers. The fastest previously known algorithm has exponential expected running time. Our algorithm is polynomial, requiring an expected O(n 4 ) operations. Applications of this algorithm include the elimination of critical sections from concurrent data structures and the construction of asymptotically unbiased shared coins.
The Topological Structure of Asynchronous Computability
 JOURNAL OF THE ACM
, 1996
"... We give necessary and sufficient combinatorial conditions characterizing the tasks that can be solved by asynchronous processes, of which all but one can fail, that communicate by reading and writing a shared memory. We introduce a new formalism for tasks, based on notions from classical algebra ..."
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Cited by 117 (11 self)
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We give necessary and sufficient combinatorial conditions characterizing the tasks that can be solved by asynchronous processes, of which all but one can fail, that communicate by reading and writing a shared memory. We introduce a new formalism for tasks, based on notions from classical algebraic and combinatorial topology, in which a task's possible input and output values are each associated with highdimensional geometric structures called simplicial complexes. We characterize computability in terms of the topological properties of these complexes. This characterization has a surprising geometric interpretation: a task is solvable if and only if the complex representing the task's allowable inputs can be mapped to the complex representing the task's allowable outputs by a function satisfying certain simple regularity properties. Our formalism thus replaces the "operational" notion of a waitfree decision task, expressed in terms of interleaved computations unfolding ...
Composite Registers
 Distributed Computing
, 1993
"... We introduce a shared data object, called a composite register, that generalizes the notion of an atomic register. A composite register is an arraylike shared data object that is partitioned into a number of components. An operation of a composite register either writes a value to a single componen ..."
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Cited by 108 (7 self)
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We introduce a shared data object, called a composite register, that generalizes the notion of an atomic register. A composite register is an arraylike shared data object that is partitioned into a number of components. An operation of a composite register either writes a value to a single component or reads the values of all components. A composite register reduces to an ordinary atomic register when there is only one component. In this paper, we show that multireader, singlewriter atomic registers can be used to implement a composite register in which there is only one writer per component. In a related paper, we show how to use the composite register construction of this paper to implement a composite register with multiple writers per component. These two constructions show that it is possible to implement a shared memory that can be read in its entirety in a single snapshot operation, without using mutual exclusion. Keywords: atomicity, atomic register, composite register, conc...
Contention in Shared Memory Algorithms
, 1993
"... Most complexitymeasures for concurrent algorithms for asynchronous sharedmemory architectures focus on process steps and memory consumption. In practice, however, performance of multiprocessor algorithms is heavily influenced by contention, the extent to which processes access the same location at t ..."
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Cited by 63 (1 self)
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Most complexitymeasures for concurrent algorithms for asynchronous sharedmemory architectures focus on process steps and memory consumption. In practice, however, performance of multiprocessor algorithms is heavily influenced by contention, the extent to which processes access the same location at the same time. Nevertheless, even though contention is one of the principal considerations affecting the performance of real algorithms on real multiprocessors, there are no formal tools for analyzing the contention of asynchronous sharedmemory algorithms. This paper introduces the first formal complexity model for contention in multiprocessors. We focus on the standard multiprocessor architecture in which n asynchronous processes communicate by applying read, write, and readmodifywrite operations to a shared memory. We use our model to derive two kinds of results: (1) lower bounds on contention for well known basic problems such as agreement and mutual exclusion, and (2) tradeoffs betwe...
Bounded concurrent time stamps systems are constructible
 In Proc. 21st ACM Symp. on Theory of Computing. ACM SIGACT, ACM
, 1989
"... Concurrent time stamping is at the heart of solu tions to some of the most fundamental problems in distributed computing. Based on concurrent timestampsystems, elegant and simple solu tions to core problems such as fcf,mutual exclusion, construction of a multireadermulti writer atomic register. ..."
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Cited by 47 (5 self)
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Concurrent time stamping is at the heart of solu tions to some of the most fundamental problems in distributed computing. Based on concurrent timestampsystems, elegant and simple solu tions to core problems such as fcf,mutual exclusion, construction of a multireadermulti writer atomic register. probabilistic consensus,.. were developed. Unfortunmely, the only known implementation of a concurrent time stamp sys tem has been theoretically unsatisfying since it requires unbounded size timestamps, in other words, unbounded memory. Not knowing if bounded concurrenttimestampsystems are at all constructible, researchers were led to con structing complicated problemspecific solutions to replace the simple unbounded ones. In this work for the first time, a bounded iruplemen tation of a concurrenttimestampsystem is pre sented. It provides a modular unboundedtobounded transformation of the simple unbounded solutions to prob1err such as above It al lows solutions to two formerly open problems, the boundedprobabilisticconsensus problem of AbrahamBon [A88] and the fifotexclusion prob
Time and SpaceEfficient Randomized Consensus
 Journal of Algorithms
, 1992
"... A protocol is presented which solves the randomized consensus problem[9] for shared memory. The protocol uses a total of O(p 2 +n) worstcase expected increment, decrement and read operations on a set of three shared O(logn)bit counters, where p is the number of active processors and n is the ..."
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Cited by 46 (12 self)
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A protocol is presented which solves the randomized consensus problem[9] for shared memory. The protocol uses a total of O(p 2 +n) worstcase expected increment, decrement and read operations on a set of three shared O(logn)bit counters, where p is the number of active processors and n is the total number of processors. It requires less space than previous polynomialtime consensus protocols[6, 7], and is faster when not all of the processors participate in the protocol. A modified version of the protocol yields a weak shared coin whose bias is guaranteed to be in the range 1=2 \Sigma ffl regardless of scheduler behavior, and which is the first such protocol for the sharedmemory model to guarantee that all processors agree on the outcome of the coin. 1 1.
Parallel Algorithms with Processor Failures and Delays
, 1995
"... We study efficient deterministic parallel algorithms on two models: restartable failstop CRCW PRAMs and asynchronous PRAMs. In the first model, synchronous processors are subject to arbitrary stop failures and restarts determined by an online adversary and involving loss of private but not shared ..."
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Cited by 42 (7 self)
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We study efficient deterministic parallel algorithms on two models: restartable failstop CRCW PRAMs and asynchronous PRAMs. In the first model, synchronous processors are subject to arbitrary stop failures and restarts determined by an online adversary and involving loss of private but not shared memory; the complexity measures are completed work (where processors are charged for completed fixedsize update cycles) and overhead ratio (completed work amortized over necessary work and failures). In the second model, the result of the computation is a serializaton of the actions of the processors determined by an online adversary; the complexity measure is total work (number of steps taken by all processors). Despite their differences the two models share key algorithmic techniques. We present new algorithms for the WriteAll problem (in which P processors write ones into an array of size N ) for the two models. These algorithms can be used to implement a simulation strategy for any N ...
Hundreds of Impossibility Results for Distributed Computing
 Distributed Computing
, 2003
"... We survey results from distributed computing that show tasks to be impossible, either outright or within given resource bounds, in various models. The parameters of the models considered include synchrony, faulttolerance, different communication media, and randomization. The resource bounds refe ..."
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Cited by 40 (4 self)
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We survey results from distributed computing that show tasks to be impossible, either outright or within given resource bounds, in various models. The parameters of the models considered include synchrony, faulttolerance, different communication media, and randomization. The resource bounds refer to time, space and message complexity. These results are useful in understanding the inherent difficulty of individual problems and in studying the power of different models of distributed computing.