Parallel Computing. The simultaneous execution of the same task (split up and specially adapted) on multiple processors in order to obtain results faster. Editorial Reviews. Book Description. This comprehensive introduction to parallel computing is for students and practitioners alike. It covers both theoretical and. Read "Introduction to Parallel Computing" by Zbigniew J. Czech available from Rakuten Kobo. Sign up today and get $5 off your first download. The constantly.
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ParCo marks a quarter of a century of the international conferences on parallel computing that started in Berlin in The aim of the conference is to give. An Introduction to Parallel Programming is the first undergraduate text to directly address compiling and running parallel programs on the new multi-core and. Compre Parallel Programming with MPI (English Edition) de Peter Pacheco na taunipesetis.cf Confira também os eBooks mais vendidos, lançamentos e livros .
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Similar Items Related Subjects: Linked Data More info about Linked Data. Primary Entity http: MediaObject , schema: A new implementation of a force decomposition method for parallel molecular dynamics simulations is presented.
It is based on a geometrical decomposition of the influence matrix where sections are dynamically reorganized during the simulation in order to maintain a good load balance. Furthermore space filling curves are used to sort particles in space, which makes memory access more efficient and furthermore reduces communication between processors due to better locality.
Benchmark runs are presented which shows in improvement in scalability due to well balanced work on the processors. The simulation of fluid flow on the nano-scale in the field of process engineering involves a large number of relatively small molecules.
The systems we are simulating can be modelled using rigid molecular models assembled from sites with non-bonded short-range pair potentials Each of the sites is described by a set of parameters which are required for the calculation of interactions between sites of the same type.
For the interaction of unequal sites, mixed parameter sets have to be calculated. This has to be done for each possible pair of sites. We describe an approach to precalculate and store those mixed parameter sets in a stream, which allows efficient access and gives the flexibility to add new site types easily. Another focus of our work has been on software engineering techniques. Using the adapter design pattern, we achieved a complete decoupling of the physical parts of the simulation e. This eases the further concurrent development of the software and reduces the complexity of the different modules.
It also gives us the opportunity to swap modules in a plug-in like fashion. We discuss an extension of the Massively Parallel Quantum Computer Simulator by a gate level error model which covers operational errors and decoherence.
Applying this error model to the Quantum Fourier Transformation the kernel of Shor's algorithm and Grover's quantum search algorithm, one finds that the QFT circuit is more robust to operational inaccuracies than Grover's algorithm on comparable scales.
Critical parameters can be derived which give a first estimate of tolerable error thresholds. At present ion traps are regarded as the most promising technology for the realization of quantum computers due to the long coherence time of trapped ions. We discuss Hamiltonian based dynamical ion-trap simulations which have been developed in collaboration with the experimental working group of Prof.
Rainer Blatt. In contrast to standard approaches no approximations like the rotating wave approximation or an expansion in the Lamb-Dicke parameter are required which allow for very accurate simulations.
This permits to identify critical system parameters which limit the stability of the experiment. A typical commodity camera rarely supports selecting a region of interest to reduce bandwidth, and depending on the extent of image processing, a single CPU may not be sufficient to process data from the camera. Further, such cameras often lack support for synchronized inter-camera image capture, making it difficult to relate images from different cameras.
This paper presents a scalable, dedicated parallel camera system for detecting objects in front of a wall-sized, high-resolution, tiled display. The system determines the positions of detected objects, and uses them to interact with applications. Since a single camera can saturate either the bus or CPU, depending on its characteristics and the image processing complexity, the system supports configuring the number of cameras per computer according to bandwidth and processing needs.
To minimize image processing latency, the system focuses only on detecting where objects are, rather than what they are, thus reducing the problem's complexity. To overcome the lack of synchronized cameras, short periods of waiting are used. An experimental study using 16 cameras has shown that the system achieves acceptable latency for applications such as 3D games.
Virtual Reality has shown to be a useful tool in the visualization of complex flow simulation data sets. Maintaining interactivity for the user exploring unstructured, time-varying data demands parallel computing power.
We propose a decoupling of interactive and non-interactive tasks to avoid latencies. We introduce an optimized resampling algorithm for unstructured grids which remains scalable using hybrid parallelization.
With a resampled region-of-interest, interactive execution of arbitrary visualization techniques is made possible. To validate findings, the user can access different error metrics made during resampling. In this work we analyze the performance of the Weather Research and Forecasting WRF model using both empirical data and an accurate analytic performance model. WRF is a large-scale mesoscale numerical weather prediction system designed for both operational forecasting and atmospheric research.
In addition, we develop a performance model of WRF that is validated against these two systems and that exhibits high prediction accuracy. The model is then used to examine the performance of a near-term future generation supercomputer.
This paper presents a framework based on an user driven methodology to obtain analytical models on parallel systems and, in particular, clusters.
This framework consists of two interconnected stages. In the first one, the analyst instruments the source code and some performance parameters are monitored.
In the second one, the monitored data are used to obtain an analytical model using statistical processes. The main functionalities added to the analysis stage include an automatic fit process that provides accurate performance models and the automatic data collection from monitoring. Some examples are used to show the automatic fit process. The accuracy of the models is compared with a complexity study of the selected examples.
Computational force, also called computational intensity, is a unifying concept for understanding the performance of parallel numerical algorithms.
Dimensional analysis reduces a formula for execution time, from a paper by Stewart, to an exercise in differential geometry for a single efficiency surface. Different machines move on the surface along different paths defined by curvilinear coordinates that depend on ratios of hardware forces to software forces.
Periscope is a distributed automatic online performance analysis system for large scale parallel systems. It consists of a set of analysis agents distributed on the parallel machine.
This article presents the approach taken on the ALTIX supercomputer at LRZ to distribute the analysis agents and the application processes on to the set of processors assigned to a parallel job by the batch scheduling system. An optimized mapping reducing the distance between the analysis agents and the application processes is computed based on the topology information of the processors. This mapping is then implemented via the dplace command on the Altix.
This paper describes case studies with the Eden Trace Viewer EdenTV , a post-mortem trace analysis and visualisation tool for the parallel functional language Eden. It shows program executions in terms of Eden's abstract units of computation instead of providing a machine-oriented low level view like common tools for parallelism analysis do. We show how typical inefficiencies in parallel functional programs due to delayed evaluation, or unbalanced workload can be detected by analysing the trace visualisations.
In the recent years, strong efforts have been dedicated on the study of applications' execution phases. In this paper, we show an approach focused on the automatic detection of the phases on MPI applications' execution. This detection is based on Wavelet Analysis, which provides a meaningful and fast methodology.