953 resultados para OPENMP PROGRAMMING


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This paper presents a new parallel methodology for calculating the determinant of matrices of the order n, with computational complexity O(n), using the Gauss-Jordan Elimination Method and Chio's Rule as references. We intend to present our step-by-step methodology using clear mathematical language, where we will demonstrate how to calculate the determinant of a matrix of the order n in an analytical format. We will also present a computational model with one sequential algorithm and one parallel algorithm using a pseudo-code.

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The process of developing software that takes advantage of multiple processors is commonly referred to as parallel programming. For various reasons, this process is much harder than the sequential case. For decades, parallel programming has been a problem for a small niche only: engineers working on parallelizing mostly numerical applications in High Performance Computing. This has changed with the advent of multi-core processors in mainstream computer architectures. Parallel programming in our days becomes a problem for a much larger group of developers. The main objective of this thesis was to find ways to make parallel programming easier for them. Different aims were identified in order to reach the objective: research the state of the art of parallel programming today, improve the education of software developers about the topic, and provide programmers with powerful abstractions to make their work easier. To reach these aims, several key steps were taken. To start with, a survey was conducted among parallel programmers to find out about the state of the art. More than 250 people participated, yielding results about the parallel programming systems and languages in use, as well as about common problems with these systems. Furthermore, a study was conducted in university classes on parallel programming. It resulted in a list of frequently made mistakes that were analyzed and used to create a programmers' checklist to avoid them in the future. For programmers' education, an online resource was setup to collect experiences and knowledge in the field of parallel programming - called the Parawiki. Another key step in this direction was the creation of the Thinking Parallel weblog, where more than 50.000 readers to date have read essays on the topic. For the third aim (powerful abstractions), it was decided to concentrate on one parallel programming system: OpenMP. Its ease of use and high level of abstraction were the most important reasons for this decision. Two different research directions were pursued. The first one resulted in a parallel library called AthenaMP. It contains so-called generic components, derived from design patterns for parallel programming. These include functionality to enhance the locks provided by OpenMP, to perform operations on large amounts of data (data-parallel programming), and to enable the implementation of irregular algorithms using task pools. AthenaMP itself serves a triple role: the components are well-documented and can be used directly in programs, it enables developers to study the source code and learn from it, and it is possible for compiler writers to use it as a testing ground for their OpenMP compilers. The second research direction was targeted at changing the OpenMP specification to make the system more powerful. The main contributions here were a proposal to enable thread-cancellation and a proposal to avoid busy waiting. Both were implemented in a research compiler, shown to be useful in example applications, and proposed to the OpenMP Language Committee.

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This paper describes our plans to evaluate the present state of affairs concerning parallel programming and its systems. Three subprojects are proposed: a survey among programmers and scientists, a comparison of parallel programming systems using a standard set of test programs, and a wiki resource for the parallel programming community - the Parawiki. We would like to invite you to participate and turn these subprojects into true community efforts.

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In this publication, we report on an online survey that was carried out among parallel programmers. More than 250 people worldwide have submitted answers to our questions, and their responses are analyzed here. Although not statistically sound, the data we provide give useful insights about which parallel programming systems and languages are known and in actual use. For instance, the collected data indicate that for our survey group MPI and (to a lesser extent) C are the most widely used parallel programming system and language, respectively.

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An overview is given of the lessons learned from the introduction of multi-threading using OpenMP in tmLQCD. In particular, programming style, performance measurements, cache misses, scaling, thread distribution for hybrid codes, race conditions, the overlapping of communication and computation and the measurement and reduction of certain overheads are discussed. Performance measurements and sampling profiles are given for different implementations of the hopping matrix computational kernel.

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A raíz de la aparición de los procesadores dotados de varios “cores”, la programación paralela, un concepto que, por otra parte no era nada nuevo y se conocía desde hace décadas, sufrió un nuevo impulso, pues se creía que se podía superar el techo tecnológico que había estado limitando el rendimiento de esta programación durante años. Este impulso se ha ido manteniendo hasta la actualidad, movido por la necesidad de sistemas cada vez más potentes y gracias al abaratamiento de los costes de fabricación. Esta tendencia ha motivado la aparición de nuevo software y lenguajes con componentes orientados precisamente al campo de la programación paralela. Este es el caso del lenguaje Go, desarrollado por Google y lanzado en 2009. Este lenguaje se basa en modelos de concurrencia que lo hacen muy adecuados para abordar desarrollos de naturaleza paralela. Sin embargo, la programación paralela es un campo complejo y heterogéneo, y los programadores son reticentes a utilizar herramientas nuevas, en beneficio de aquellas que ya conocen y les son familiares. Un buen ejemplo son aquellas implementaciones de lenguajes conocidos, pero orientadas a programación paralela, y que siguen las directrices de un estándar ampliamente reconocido y aceptado. Este es el caso del estándar OpenMP, un Interfaz de Programación de Aplicaciones (API) flexible, portable y escalable, orientado a la programación paralela multiproceso en arquitecturas multi-core o multinucleo. Dicho estándar posee actualmente implementaciones en los lenguajes C, C++ y Fortran. Este proyecto nace como un intento de aunar ambos conceptos: un lenguaje emergente con interesantes posibilidades en el campo de la programación paralela, y un estándar reputado y ampliamente extendido, con el que los programadores se encuentran familiarizados. El objetivo principal es el desarrollo de un conjunto de librerías del sistema (que engloben directivas de compilación o pragmas, librerías de ejecución y variables de entorno), soportadas por las características y los modelos de concurrencia propios de Go; y que añadan funcionalidades propias del estándar OpenMP. La idea es añadir funcionalidades que permitan programar en lenguaje Go utilizando la sintaxis que OpenMP proporciona para otros lenguajes, como Fortan y C/C++ (concretamente, similar a esta última), y, de esta forma, dotar al usuario de Go de herramientas para programar estructuras de procesamiento paralelo de forma sencilla y transparente, de la misma manera que lo haría utilizando C/C++.---ABSTRACT---As a result of the appearance of processors equipped with multiple "cores ", parallel programming, a concept which, moreover, it was not new and it was known for decades, suffered a new impulse, because it was believed they could overcome the technological ceiling had been limiting the performance of this program for years. This impulse has been maintained until today, driven by the need for ever more powerful systems and thanks to the decrease in manufacturing costs. This trend has led to the emergence of new software and languages with components guided specifically to the field of parallel programming. This is the case of Go language, developed by Google and released in 2009. This language is based on concurrency models that make it well suited to tackle developments in parallel nature. However, parallel programming is a complex and heterogeneous field, and developers are reluctant to use new tools to benefit those who already know and are familiar. A good example are those implementations from well-known languages, but parallel programming oriented, and witch follow the guidelines of a standard widely recognized and accepted. This is the case of the OpenMP standard, an application programming interface (API), flexible, portable and scalable, parallel programming oriented, and designed for multi-core architectures. This standard currently has implementations in C, C ++ and Fortran. This project was born as an attempt to combine two concepts: an emerging language, with interesting possibilities in the field of parallel programming, and a reputed and widespread standard, with which programmers are familiar with. The main objective is to develop a set of system libraries (which includes compiler directives or pragmas, runtime libraries and environment variables), supported by the characteristics and concurrency patterns of Go; and that add custom features from the OpenMP standard. The idea is to add features that allow programming in Go language using the syntax OpenMP provides for other languages, like Fortran and C / C ++ (specifically, similar to the latter ), and, in this way, provide Go users with tools for programming parallel structures easily and, in the same way they would using C / C ++.

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Processors with large numbers of cores are becoming commonplace. In order to utilise the available resources in such systems, the programming paradigm has to move towards increased parallelism. However, increased parallelism does not necessarily lead to better performance. Parallel programming models have to provide not only flexible ways of defining parallel tasks, but also efficient methods to manage the created tasks. Moreover, in a general-purpose system, applications residing in the system compete for the shared resources. Thread and task scheduling in such a multiprogrammed multithreaded environment is a significant challenge. In this thesis, we introduce a new task-based parallel reduction model, called the Glasgow Parallel Reduction Machine (GPRM). Our main objective is to provide high performance while maintaining ease of programming. GPRM supports native parallelism; it provides a modular way of expressing parallel tasks and the communication patterns between them. Compiling a GPRM program results in an Intermediate Representation (IR) containing useful information about tasks, their dependencies, as well as the initial mapping information. This compile-time information helps reduce the overhead of runtime task scheduling and is key to high performance. Generally speaking, the granularity and the number of tasks are major factors in achieving high performance. These factors are even more important in the case of GPRM, as it is highly dependent on tasks, rather than threads. We use three basic benchmarks to provide a detailed comparison of GPRM with Intel OpenMP, Cilk Plus, and Threading Building Blocks (TBB) on the Intel Xeon Phi, and with GNU OpenMP on the Tilera TILEPro64. GPRM shows superior performance in almost all cases, only by controlling the number of tasks. GPRM also provides a low-overhead mechanism, called “Global Sharing”, which improves performance in multiprogramming situations. We use OpenMP, as the most popular model for shared-memory parallel programming as the main GPRM competitor for solving three well-known problems on both platforms: LU factorisation of Sparse Matrices, Image Convolution, and Linked List Processing. We focus on proposing solutions that best fit into the GPRM’s model of execution. GPRM outperforms OpenMP in all cases on the TILEPro64. On the Xeon Phi, our solution for the LU Factorisation results in notable performance improvement for sparse matrices with large numbers of small blocks. We investigate the overhead of GPRM’s task creation and distribution for very short computations using the Image Convolution benchmark. We show that this overhead can be mitigated by combining smaller tasks into larger ones. As a result, GPRM can outperform OpenMP for convolving large 2D matrices on the Xeon Phi. Finally, we demonstrate that our parallel worksharing construct provides an efficient solution for Linked List processing and performs better than OpenMP implementations on the Xeon Phi. The results are very promising, as they verify that our parallel programming framework for manycore processors is flexible and scalable, and can provide high performance without sacrificing productivity.

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This paper addresses the non-preemptive single machine scheduling problem to minimize total tardiness. We are interested in the online version of this problem, where orders arrive at the system at random times. Jobs have to be scheduled without knowledge of what jobs will come afterwards. The processing times and the due dates become known when the order is placed. The order release date occurs only at the beginning of periodic intervals. A customized approximate dynamic programming method is introduced for this problem. The authors also present numerical experiments that assess the reliability of the new approach and show that it performs better than a myopic policy.

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The economic occupation of an area of 500 ha for Piracicaba was studied with the irrigated cultures of maize, tomato, sugarcane and beans, having used models of deterministic linear programming and linear programming including risk for the Target-Motad model, where two situations had been analyzed. In the deterministic model the area was the restrictive factor and the water was not restrictive for none of the tested situations. For the first situation the gotten maximum income was of R$ 1,883,372.87 and for the second situation it was of R$ 1,821,772.40. In the model including risk a producer that accepts risk can in the first situation get the maximum income of R$ 1,883,372. 87 with a minimum risk of R$ 350 year(-1), and in the second situation R$ 1,821,772.40 with a minimum risk of R$ 40 year(-1). Already a producer averse to the risk can get in the first situation a maximum income of R$ 1,775,974.81 with null risk and for the second situation R$ 1.707.706, 26 with null risk, both without water restriction. These results stand out the importance of the inclusion of the risk in supplying alternative occupations to the producer, allowing to a producer taking of decision considered the risk aversion and the pretension of income.

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These notes follow on from the material that you studied in CSSE1000 Introduction to Computer Systems. There you studied details of logic gates, binary numbers and instruction set architectures using the Atmel AVR microcontroller family as an example. In your present course (METR2800 Team Project I), you need to get on to designing and building an application which will include such a microcontroller. These notes focus on programming an AVR microcontroller in C and provide a number of example programs to illustrate the use of some of the AVR peripheral devices.

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Background. Age-related motor slowing may reflect either motor programming deficits, poorer movement execution, or mere strategic preferences for online guidance of movement. We controlled such preferences, limiting the extent to which movements could be programmed. Methods. Twenty-four young and 24 older adults performed a line drawing task that allowed movements to he prepared in advance in one case (i.e., cue initially available indicating target location) and not in another (i.e., no cue initially available as to target location). Participants connected large or small targets illuminated by light-emitting diodes upon a graphics tablet that sampled pen tip position at 200 Hz. Results. Older adults had a disproportionate difficulty initiating movement when prevented from programming in advance. Older adults produced slower, less efficient movements, particularly when prevented from programming under greater precision requirements. Conclusions. The slower movements of older adults do not simply reflect a preference for online control, as older adults have less efficient movements when forced to reprogram their movements. Age-related motor slowing kinematically resembles that seen in patients with cerebellar dysfunction.

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This paper presents the unique collection of additional features of Qu-Prolog, a variant of the Al programming language Prolog, and illustrates how they can be used for implementing DAI applications. By this we mean applications comprising communicating information servers, expert systems, or agents, with sophisticated reasoning capabilities and internal concurrency. Such an application exploits the key features of Qu-Prolog: support for the programming of sound non-clausal inference systems, multi-threading, and high level inter-thread message communication between Qu-Prolog query threads anywhere on the internet. The inter-thread communication uses email style symbolic names for threads, allowing easy construction of distributed applications using public names for threads. How threads react to received messages is specified by a disjunction of reaction rules which the thread periodically executes. A communications API allows smooth integration of components written in C, which to Qu-Prolog, look like remote query threads.

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1. Establishing biological control agents in the field is a major step in any classical biocontrol programme, yet there are few general guidelines to help the practitioner decide what factors might enhance the establishment of such agents. 2. A stochastic dynamic programming (SDP) approach, linked to a metapopulation model, was used to find optimal release strategies (number and size of releases), given constraints on time and the number of biocontrol agents available. By modelling within a decision-making framework we derived rules of thumb that will enable biocontrol workers to choose between management options, depending on the current state of the system. 3. When there are few well-established sites, making a few large releases is the optimal strategy. For other states of the system, the optimal strategy ranges from a few large releases, through a mixed strategy (a variety of release sizes), to many small releases, as the probability of establishment of smaller inocula increases. 4. Given that the probability of establishment is rarely a known entity, we also strongly recommend a mixed strategy in the early stages of a release programme, to accelerate learning and improve the chances of finding the optimal approach.