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Transactional Memory: Architectural Support for LockFree Data Structures
"... A shared data structure is lockfree if its operations do not require mutual exclusion. If one process is interrupted in the middle of an operation, other processes will not be prevented from operating on that object. In highly concurrent systems, lockfree data structures avoid common problems asso ..."
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Cited by 1031 (27 self)
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based on mutual exclusion. Transactional memory allows programmers to define customized readmodifywrite operations that apply to multiple, independentlychosen words of memory. It is implemented by straightforward extensions to any multiprocessor cachecoherence protocol. Simulation results show
Trace Scheduling: A Technique for Global Microcode Compaction
 IEEE TRANSACTIONS ON COMPUTERS
, 1981
"... Microcode compaction is the conversion of sequential microcode into efficient parallel (horizontal) microcode. Local compaction techniques are those whose domain is basic blocks of code, while global methods attack code with a general flow control. Compilation of highlevel microcode languages int ..."
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Cited by 683 (5 self)
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simplified and straightforward model of microinstructions. Guides to the extension to more general models are given.
Efficient Algorithms for Mining Outliers from Large Data Sets
, 2000
"... In this paper, we propose a novel formulation for distancebased outliers that is based on the distance of a point from its k th nearest neighbor. We rank each point on the basis of its distance to its k th nearest neighbor and declare the top n points in this ranking to be outliers. In addition ..."
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Cited by 322 (0 self)
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. In addition to developing relatively straightforward solutions to finding such outliers based on the classical nestedloop join and index join algorithms, we develop a highly efficient partitionbased algorithm for mining outliers. This algorithm first partitions the input data set into disjoint subsets
ULDBs: Databases with uncertainty and lineage
 IN VLDB
, 2006
"... This paper introduces ULDBs, an extension of relational databases with simple yet expressive constructs for representing and manipulating both lineage and uncertainty. Uncertain data and data lineage are two important areas of data management that have been considered extensively in isolation, howev ..."
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Cited by 310 (32 self)
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This paper introduces ULDBs, an extension of relational databases with simple yet expressive constructs for representing and manipulating both lineage and uncertainty. Uncertain data and data lineage are two important areas of data management that have been considered extensively in isolation
Exemplar dynamics: Word frequency, lenition and contrast
 In
, 2001
"... Exemplar theory was first developed as a model of similarity and classification in perception. In this paper, the theory is extended to model speech production as well as speech perception. Straightforward extension of the model provides a formal framework for thinking about the quantitative predict ..."
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Cited by 243 (7 self)
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Exemplar theory was first developed as a model of similarity and classification in perception. In this paper, the theory is extended to model speech production as well as speech perception. Straightforward extension of the model provides a formal framework for thinking about the quantitative
A BGPbased Mechanism for LowestCost Routing
, 2002
"... The routing of traffic between... this paper, we address the problem of interdomain routing from a mechanismdesign point of view. The application of mechanismdesign principles to the study of routing is the subject of earlier work by Nisan and Ronen [15] and Hershberger and Suri [11]. In this pape ..."
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Cited by 268 (16 self)
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that is a straightforward extension to BGP and causes only modest increases in routingtable size and convergence time (in contrast with the centralized algorithms used in [15,11]). This approach of using an existing protocol as a substrate for distributed computation may prove useful in future development
Weak Convergence And Optimal Scaling Of Random Walk Metropolis Algorithms
, 1994
"... This paper considers the problem of scaling the proposal distribution of a multidimensional random walk Metropolis algorithm, in order to maximize the efficiency of the algorithm. The main result is a weak convergence result as the dimension of a sequence of target densities, n, converges to infinit ..."
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Cited by 280 (34 self)
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to infinity. When the proposal variance is appropriately scaled according to n, the sequence of stochastic processes formed by the first component of each Markov chain, converge to the appropriate limiting Langevin diffusion process. The limiting diffusion approximation admits a straightforward efficiency
A Scalable Approach to ThreadLevel Speculation
 IN PROCEEDINGS OF THE 27TH ANNUAL INTERNATIONAL SYMPOSIUM ON COMPUTER ARCHITECTURE
, 2000
"... While architects understandhow to build costeffective parallel machines across a wide spectrum of machine sizes (ranging from within a single chip to largescale servers), the real challenge is how to easily create parallel software to effectively exploit all of this raw performancepotential. One p ..."
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Cited by 232 (20 self)
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scales to any machine size because it is a straightforward extension of writeback invalidationbased cache coherence (which itself scales both up and down). Our experimental results demonstrate that our scheme performs well on both singlechip multiprocessors and on largerscale machines where
CoArray Fortran for parallel programming
 ACM FORTRAN FORUM
, 1998
"... CoArray Fortran, formerly known as F, is a small extension of Fortran 95 for parallel processing. A CoArray Fortran program is interpreted as if it were replicated a number of times and all copies were executed asynchronously. Each copy has its own set of data objects and is termed an image. The ..."
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Cited by 278 (7 self)
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CoArray Fortran, formerly known as F, is a small extension of Fortran 95 for parallel processing. A CoArray Fortran program is interpreted as if it were replicated a number of times and all copies were executed asynchronously. Each copy has its own set of data objects and is termed an image
Hidden Markov models for sequence analysis: extension and analysis of the basic method
, 1996
"... Hidden Markov models (HMMs) are a highly effective means of modeling a family of unaligned sequences or a common motif within a set of unaligned sequences. The trained HMM can then be used for discrimination or multiple alignment. The basic mathematical description of an HMM and its expectationmaxi ..."
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Cited by 219 (23 self)
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maximization training procedure is relatively straightforward. In this paper, we review the mathematical extensions and heuristics that move the method from the theoretical to the practical. Then, we experimentally analyze the effectiveness of model regularization, dynamic model modification, and optimization
Results 1  10
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