NASA Technical Reports Server (Ntrs) 19910010419: the Force: a Highly Portable parallel programming Language by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 19910010419: the Force: a Highly Portable parallel programming Language by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 19890020413: the Force: a Portable parallel programming Language Supporting Computational Structural Mechanics by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 19890020413: the Force: a Portable parallel programming Language Supporting Computational Structural Mechanics by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20010097883: parallel programming Strategies for Irregular Adaptive Applications by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20010097883: parallel programming Strategies for Irregular Adaptive Applications by NASA Technical Reports Server (Ntrs); published by
Composability is a key component to improve programmers' productivity in writing fast market-expanding applications such as parallel machine learning algorithms and big data analytics. These applications exhibit b...
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Composability is a key component to improve programmers' productivity in writing fast market-expanding applications such as parallel machine learning algorithms and big data analytics. These applications exhibit both regular and irregular compute patterns, and are often combined with other functions or libraries to compose a larger program. However, composable parallel processing has taken a back seat in many existing parallel programming libraries, making it difficult to achieve modularity in large-scale parallel programs. In this paper, we introduce a new parallel task programming library using composable tasking graphs. Our library efficiently supports task parallelism together with an intuitive task graph construction and flexible execution API set to enable reusable and composable task dependency graphs. Developers can quickly compose a large parallel program from small and modular parallel building blocks, and easily deploy the program on a multicore machine. We have evaluated our library on real-world applications. Experimental results showed our library can achieve comparable performance to Intel Threading Building Blocks with less coding effort.
NASA Technical Reports Server (Ntrs) 20000068916: Portable parallel programming for the Dynamic Load Balancing of Unstructured Grid Applications by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20000068916: Portable parallel programming for the Dynamic Load Balancing of Unstructured Grid Applications by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20030025348: Architecture-Adaptive Computing Environment: a Tool for Teaching parallel programming by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20030025348: Architecture-Adaptive Computing Environment: a Tool for Teaching parallel programming by NASA Technical Reports Server (Ntrs); published by
parallel programming is a field of science with a great potential nowadays due to the development of advanced computers architectures. Appropriate usage of this tool can be therefore highly beneficial in multimedia ap...
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ISBN:
(纸本)9781538623718
parallel programming is a field of science with a great potential nowadays due to the development of advanced computers architectures. Appropriate usage of this tool can be therefore highly beneficial in multimedia applications and significantly decreases the time of calculations. In this article, we analyze how the speed of calculations is influenced by the usage of parallel algorithms in image filtering processes. We present a method based on multithreading and the division of the image for rectangles. The filter is applied parallel on each part of the image. Results show that in some cases our proposition can bring over 90% benefit when compared to the classical approach.
The paper focuses on the development of a numerical code for the computation of basins of attraction by using the parallel programming. Two different approaches based on the massage passing interface (MPI) standard ar...
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The paper focuses on the development of a numerical code for the computation of basins of attraction by using the parallel programming. Two different approaches based on the massage passing interface (MPI) standard are presented;the performance analysis presented encourages us to use a massive communication between nodes only for a few-cores architecture. The critical issues arising from the study of a generic dynamical system are discussed while the computation of basins is performed on a benchmark system described by Duffing's equation. We paid attention at the optimization of the computing time as well as the work time load on each node in order to develop a performing and portable code. For the presented codes, both the scalability with an implementation on a professional cluster and the capabilities of the parallelism in the elaborations of basins with a large set of initial conditions have been tested. (C) 2015 Elsevier Ltd. All rights reserved.
The study of tumor growth biology with computer-based models is currently an area of active research. Different simulation techniques can be used to describe the complexity of any real tumor behavior, among these, &qu...
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The study of tumor growth biology with computer-based models is currently an area of active research. Different simulation techniques can be used to describe the complexity of any real tumor behavior, among these, "cellular automata"-based simulations provide an accurate tumor growth graphical representation while, at the same time, keep simpler the implementation of the automata as computer programs. Several authors have recently published relevant proposals, based on the latter approach, to solve tumor growth representation problem through the development of some strategies for accelerating the simulation model. These strategies achieve computational performance of cellular-models representation by the appropriate selection of data types, and the clever use of supporting data structures. However, as of today, multithreaded processing techniques and multicore processors have not been used to program cellular growth models with generality. This paper presents a new model that incorporates parallel programming for multi and manycore processors, and implements any synchronization requirement necessary to implement the solution. The proposed parallel model has been proved using Java and C++ program implementations on two different platforms: chipset Intel i5-4440 and one node of 16-processors cluster of our university. The improvement resulting from the introduction of parallelism into the model is analyzed in this paper, comparing it with the standard sequential simulation model currently used by researchers in mathematical oncology.
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