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Programming parallel computers

Xem 1-20 trên 81 kết quả Programming parallel computers
  • DAPSYS (Austrian-Hungarian Workshop on Distributed and Parallel Systems) is an international conference series with biannual events dedicated to all aspects of distributed and parallel computing. DAPSYS started under a different name in 1992 (Sopron, Hungary) as a regional meeting of Austrian and Hungarian researchers focusing on transputer-related parallel computing; a hot research topic of that time. A second workshop followed in 1994 (Budapest, Hungary).

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  • JR is a language for concurrent programming. It is an imperative language that provides explicit mechanisms for concurrency, communication, and synchronization. JR is an extension of the Java programming language with additional concurrency mechanisms based on those in the SR (Synchronizing Resources) programming language. It is suitable for writing programs for both shared- and distributed-memory applications and machines; it is, of course, also suitable for writing sequential programs.

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  • Biological macromolecules (DNA, RNA and proteins) are capable of processing physical or chemical inputs to generate outputs that parallel conventional Boolean logical operators. However, the design of functional modules that will enable these macromolecules to operate as synthetic molecular computing devices is challenging.

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  • The haplotype phasing problem tries to screen for phenotype associated genomic variations from millions of candidate data. Most of the current computer programs handle this problem with high requirements of computing power and memory.

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  • This detailed guide for programmers, developers, and computer enthusiasts shows how to get the most from parallel port in any application or project. The Visual-Basic code and circuit designs include examples that use the new enhanced (EPP) and expanded (EPC) modes.An excellent resource for Visual Basic programmers looking to interface hardware through standard ports. Anyone designing hardware to work with a parallel port is well advised to add this book to their library.

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  • Modern digital technology has made it possible to manipulate multi-dimensional signals with systems that range from simple digital circuits to advanced parallel computers. The goal of this manipulation can be divided into three categories...

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  • Computer simulation has become an essential par t of science and engineering. Digital analysis of components, in particular, is important when developing new products or optimizing designs. Today a broad spectrum of options for simulation is available; researchers use everything from basic programming languages to various high-level packages implementing advanced methods. Though each of these techniques has its own unique attributes, they all share a common concern: Can you rely on the results?...

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  • Geo-electrical tomographical software plays a crucial role in geophysical research. However, imported software is expensive and does not provide much customizability, which is essential for more advanced geophysical study. Besides, these programs are unable to exploit the full potential of modern hardware, so the running time is inadequate for large-scale geophysical surveys. It is therefore an essential task to develop domestic software for overcoming all these problems.

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  • Parallel Programming: for Multicore and Cluster Systems- P1: Innovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing....

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  • Parallel Programming: for Multicore and Cluster Systems- P2: Innovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing....

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  • Parallel Programming: for Multicore and Cluster Systems- P3: Innovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing....

    pdf10p maicon2468 17-10-2010 58 6   Download

  • Parallel Programming: for Multicore and Cluster Systems- P4: Innovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing....

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  • Parallel Programming: for Multicore and Cluster Systems- P6: Innovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing....

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  • Parallel Programming: for Multicore and Cluster Systems- P10: Innovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing....

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  • Let's begin with the picture on the front cover. You may have observed that the portra让of Alan Turing is constructed from a number of pictures ("tiles") of great computer scientists and mathematicians. Suppose you were asked in an interview to design a program that takes an 垃nage and a collection of s x s-sized tiles and produce a mosaic from the tiles that resembles the image. A good way to begin may be to partition the image into s x s-sized squares, compute the average color of each such image square, and then find the tile that is closest to it in the color space. Here distance in...

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  • This book is about the parallel programming features of .NET 4, specifically the Task Parallel Library (TPL), Parallel LINQ, and the legion of support classes that make writing parallel programs with C# simpler and easier than ever before. With the widespread use of multiprocessor and multicore computers, parallel programming has gone mainstream. Or it would

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  • Web apps would run much better if heavy calculations could be performed in the background, rather than compete with the user interface. With this book, you’ll learn how to use Web Workers to run computationally intensive JavaScript code in a thread parallel to the UI. Yes, multi-threaded programing is complicated, but Web Workers provide a simple API that helps you be productive without the complex algorithms.

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  • Parallel Implementation of MAFFT on CUDA-Enabled Graphics Hardware present a new approach to accelerat- ing MAFFT on Graphics Processing Units (GPUs) using the Compute Unified Device Architecture (CUDA) programming model. Compared with the implementations of other MSA algorithms on GPUs, parallelization of MAFFT is more challenging since the space complexity.

     

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  • The main goal of Grid programming is the study of programming models, tools, and methods that support the effective development of portable and high-performance algorithms and applications on Grid environments. Grid programming will require capabilities and properties beyond that of simple sequential programming or even parallel and distributed programming.

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  • Parallel Programming: for Multicore and Cluster Systems- P5: Innovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing....

    pdf10p maicon2468 17-10-2010 46 4   Download

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