Simulation of a hybrid model for image denoising

Carino, R.L.; Banicescu, I.; Lim, H.; Williams, N.; Kim, Seongjai

doi:10.1109/ipdps.2006.1639605

Cited by 4 publications

(2 citation statements)

References 30 publications

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“…The routine is utilized by the applications listed in Sect. 4, as well as in other work presented elsewhere [1,17,19,20]. The routine is designed to be invoked by MPI applications that contain parallel loops like y(i) = f(x(i)), i=1,2,...,N, where x() and y() are arrays of possibly complex types, and are partitioned among the processors.…”

Section: Message-passing Implementationmentioning

confidence: 99%

Dynamic load balancing with adaptive factoring methods in scientific applications

Cariño

Banicescu

2007

J Supercomput

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To improve the performance of scientific applications with parallel loops, dynamic loop scheduling methods have been proposed. Such methods address performance degradations due to load imbalance caused by predictable phenomena like nonuniform data distribution or algorithmic variance, and unpredictable phenomena such as data access latency or operating system interference. In particular, methods such as factoring, weighted factoring, adaptive weighted factoring, and adaptive factoring have been developed based on a probabilistic analysis of parallel loop iterates with variable running times. These methods have been successfully implemented in a number of applications such as: N-Body and Monte Carlo simulations, computational fluid dynamics, and radar signal processing.The focus of this paper is on adaptive weighted factoring (AWF), a method that was designed for scheduling parallel loops in time-stepping scientific applications. The main contribution of the paper is to relax the time-stepping requirement, a modification that allows the AWF to be used in any application with a parallel loop. The modification further allows the AWF to adapt to load imbalance that may occur during loop execution. Results of experiments to compare the performance of the modified AWF with the performance of the other loop scheduling methods in the context of three nontrivial applications reveal that the performance of the modified method is

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Section: Message-passing Implementationmentioning

confidence: 99%

Dynamic load balancing with adaptive factoring methods in scientific applications

Cariño

Banicescu

2007

J Supercomput

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“…The technique is encapsulated in a routine which is invoked as repeatedly with various combinations of some of the arguments. Results of the investigations are reported in [12]. The application falls under the category of a 1D-loop.…”

Section: Image Denoisingmentioning

confidence: 99%

A Dynamic Load Balancing Tool for One and Two Dimensional Parallel Loops

Cariño

Banicescu

2006

2006 Fifth International Symposium on Parallel and Distributed Computing

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This paper describes a dynamic load balancing tool intended for computational investigators who have little familiarity with programming for a message-passing environment. Motivated by the PAR DOALL directive available in some compilers for shared-memory systems, the tool is designed to simplify the manual conversion of sequential programs containing computationally intensive loops with independent iterates into parallel programs that execute with high efficiency on general-purpose clusters. The tool implements a dynamic loop scheduling strategy to address load imbalance which may be induced by the non-uniformity of loop iterate times, and by the heterogeneity of processors. The tool is based on the Message Passing Interface library for wide availability. Timings of a nontrivial application that utilize the tool on a Linux cluster are presented to demonstrate sample achievable performance.

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