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Degree of parallelism

About: Degree of parallelism is a research topic. Over the lifetime, 1515 publications have been published within this topic receiving 25546 citations.


Papers
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Proceedings ArticleDOI
01 Dec 1991
TL;DR: An elimination approach for processing OODBs is presented that allows more processors to operate concurrently on a query, thus allowing a higher degree of parallelism in query processing.
Abstract: The authors have show previously (1989, 1991) that processing OODBs can be viewed as the manipulation of patterns of object associations. Parallel, multiple wavefront algorithms based on an identification approach for verifying association patterns have been introduced. The current paper presents an elimination approach for processing OODBs. The new approach allows more processors to operate concurrently on a query, thus allowing a higher degree of parallelism in query processing. A formal proof of the correctness of the new approach is given, and a parallel elimination algorithm for processing tree queries is presented. Some simulation results are also provided to compare the performance of the identification approach with the elimination approach. >

6 citations

Proceedings ArticleDOI
19 Apr 2017
TL;DR: In this article, the authors introduce Posterior Snapshot Isolation (PostSI), an SI mechanism that allows transactions to determine their timestamps autonomously, without relying on centralized coordination.
Abstract: Snapshot Isolation (SI) is a widely adopted concurrency control mechanism in database systems, which utilizes timestamps to resolve conflicts between transactions. However, centralized allocation of timestamps is a potential bottleneck for parallel transaction management. This bottleneck is becoming increasingly visible with the rapidly growing degree of parallelism of today's computing platforms. This paper introduces Posterior Snapshot Isolation (PostSI), an SI mechanism that allows transactions to determine their timestamps autonomously, without relying on centralized coordination. As such, PostSI can scale well, rendering it suitable for various multi-core and MPP platforms. Extensive experiments are conducted to demonstrate its advantage over existing approaches.

6 citations

Journal ArticleDOI
TL;DR: In this article, a numerical framework for pricing American options in high dimensions is proposed, which uses adaptive sparse grids to approximate the value function with a low number of points and recursively apply fast approximations of the expectation of the operator from an exercise period to the previous period.
Abstract: We introduce a novel numerical framework for pricing American options in high dimensions. Our scheme manages to alleviate the problem of dimension scaling through the use of adaptive sparse grids. We approximate the value function with a low number of points and recursively apply fast approximations of the expectation operator from an exercise period to the previous period. Given that available option databases gather several thousands of prices, there is a clear need for fast approaches in empirical work. Our method processes an entire cross section of options in a single execution and offers an immediate solution to the estimation of hedging coefficients through finite differences. It thereby brings valuable advantages over Monte Carlo simulations, which are usually considered to be the tool of choice in high dimensions, and satisfies the need for fast computation in empirical work with current databases containing thousands of prices. We benchmark our algorithm under the canonical model of Black and Scholes and the stochastic volatility model of Heston, the latter in the presence of discrete dividends. We illustrate the massive improvement of complexity scaling over dense grids with a basket option study including up to eight underlying assets. We show how the high degree of parallelism of our scheme makes it suitable for deployment on massively parallel computing units to scale to higher dimensions or further speed up the solution process.

6 citations

Book ChapterDOI
14 Jun 1998
TL;DR: This work outlines a few parallel solution methods incorporated recently in PSPARSLIB, a suite of codes for solving sparse linear systems of equations that takes a modular approach to constructing a solution method and has logic-transparent computational kernels that can be adapted to the problem at hand.
Abstract: In a parallel linear system solution, an efficient usage of a multiprocessor system is usually achieved by implementing algorithms with high degree of parallelism and good convergence properties as well as by tuning parallel codes to a particular system. Among the software tools that facilitate this development is PSPARSLIB, a suite of codes for solving sparse linear systems of equations. PSPARSLIB takes a modular approach to constructing a solution method and has logic-transparent computational kernels that can be adapted to the problem at hand. Here, we outline a few parallel solution methods incorporated recently in PSPARSLIB. We give a rationale for implementing these techniques and present several numerical experiments.

6 citations

Patent
Ba-Zhong Shen1, Tak K. Lee1
07 Jun 2007
TL;DR: Reduced complexity ARP interleaves providing flexible granularity and parallelism adaptable to any possible turbo code block size are presented in this article, where a novel means is presented by which any desired turbo code blocks size can be employed when only requiring, in only some instances, a very small number of dummy bits.
Abstract: Reduced complexity ARP (almost regular permutation) interleaves providing flexible granularity and parallelism adaptable to any possible turbo code block size. A novel means is presented by which any desired turbo code block size can be employed when only requiring, in only some instances, a very small number of dummy bits. This approach also is directly adaptable to parallel turbo decoding, in which any desired degree of parallelism can be employed. Alternatively, as few as one turbo decoder can be employed in a fully non-parallel implementation as well. Also, this approach allows for storage of a reduced number of parameters to accommodate a wide variety of interleaves.

6 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20221
202147
202048
201952
201870
201775