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We show our final GPU implementation to outperform the CPU implementation by a factor of 1700. Our top-down approach allows for quickly identifying any significant differences between the execution of the many blocks and warps. We demonstrate the strength of our approach in the context of a parallel matrix transpose kernel and a parallel 1D Haar Wavelet transform kernel. © 2013 The Author Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.

Full Text Available The use of oblique imagery has become a standard for many civil and mapping applications, thanks to the development of airborne digital multi-camera systems, as proposed by many companies. We report an overview of the actual oblique commercial systems and the workflow for the automated orientation and dense matching of large image blocks. Perspectives, potentialities, pitfalls and suggestions for achieving satisfactory results are given too. The Sankoff 4-dimensional dynamic programming matrix and we propose a two-level wavefront approach to exploit the parallelism.

Profiling results suggest that the slow speed is probably due to the memory access latency caused by the large amount of global memory transactions. Possible solutions to improve the code efficiency are discussed. Modification of the order and the combination of calcu- lations reduces the number of accesses to slow off-chip memory. Assigning tasks into multiple threads also takes memory access order into account. For a 4096-tap case, a GPU program is almost three times faster than a CPU program. Our experiments were conducted using two images captured by the DJI Phantom 3 Professional and a most recent NVIDIA GPU GTX1080.

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Microphysics plays an important role in weather and climate prediction. Several bulk water microphysics schemes are available within the WRF, with different numbers of simulated hydrometeor classes and methods American Currency Quotation Definition for estimating their size fall speeds, distributions and densities. Stony-Brook University scheme (SBU-YLIN) is a 5-class scheme with riming intensity predicted to account for mixed-phase processes.

In particular, we demonstrate that it is possible to simulate the switching currents distributions of Josephson junctions in the timescale of actual experiments. Is a parallel computing platform and programming model that was created by NVIDIA and implemented by the GPU . The framework generates compute kernels in the PTX assembler language which can be compiled to efficient GPU machine code by the NVIDIA JIT compiler. A comprehensive memory management was added to the framework so that applications, e.g. Chroma, can run unaltered on GPU clusters and supercomputers.

Usage for acceleration of development of applications and realization of algorithms of scientific and technical calculations were given which are carried out by the means of graphic processors of accelerators GeForce of the eighth generation. The recommendations on optimization of the programs using GPU were resulted. Full Text Available The Yang-Mills fields plays important role in the strong interaction, which describes the quark gluon plasma. The non-Abelian gauge theory provides the theoretical background understanding of this topic. We produce codes for the Monte Carlo generation of SU lattice gauge configurations, for the mean plaquette, for the Polyakov Loop at finite T and for the Wilson loop.

• Eventually, the serial and the parallel versions of the same animation are compared against each other on the basis of the number of image frames per second.
• To develop parallel finite difference schemes as applicable to two problems of interest to NDE community, namely heat diffusion and elastic wave propagation.
• At the same time very useful is a extensive diffusion of scientific results, joined together with the availability of a technical support for the growers.
• In the performance analysis, multi-GPU speedup and multi-GPU efficiency are applied to analyze the scalability of the multi-GPU programs.

The results in terms of runtime will be compared with non-parallelized implementations and must show a great reduction of processing time. Into numerical calculation because these consist of simple operations of matrices and vectors of single precision where actual codes were written in the C++ language. Our experimental results showed that nuclide burnup calculations with GPU have possibility of speedup by factor of 100 compared to that with CPU. Architecture in order to efficiently detect the presence of accepting cycles in a directed graph. Accepting cycle detection is the core algorithmic procedure in automata-based LTL Model Checking.

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The relative merits of the two different world model representations are shown. In particular, the experimental results show the potential of adapting the resolution of the robot and environment models to the task at hand. Is a technology developed by NVIDIA which provides a parallel computing platform and programming mo…

• In this paper we present an algorithm and its implementation which benefits from data vectorization and parallelization and which was also ported to Graphics Processi…
• Microphysics plays an important role in weather and climate prediction.
• The computer model is based on the mathematical model of a homing system and it enables the system dynamical performance analysis.

In the past few years, co-processing on Graphics Processing Units has been a disruptive technology in High Performance Computing . GPUs use the ever increasing transistor count for adding more processor cores. Therefore, GPUs are well suited for massively data parallel processing with high floating point arithmetic intensity. Thus, it is imperative to update legacy scientific applications to take advantage of this unprecedented increase in computing power.

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The target audience of the book is graduate and undergraduate students from all science and engineering disciplines who … Cores) on 290 different benchmark instances obtained from OR-Library, discrete location problems benchmark li… The benchmarks of our optimized rendering pipeline reflect its capability of generating DRRs with resolutions of vanguard cd and bond rates 2048 and 4096 at interactive and semi interactive frame-rates using an NVIDIA GeForce 970 GTX device. GPU acceleration for digitally reconstructed radiographs using bindless texture objects and CUDA /OpenGL interoperability. Accelerating the reconstruction of magnetic resonance imaging by three-dimensional dual-dictionary learning using CUDA .

This helps to apply the machine vision algorithm in real-time system. For parallel implementation of GIS algorithms over large-scale geospatial datasets. To improve its precision and stability, a robust version of the Kalman filter gbp to nzd exchange rate today has been incorporated into the flowchart. Tests showed applicability of the algorithm to practical object tracking. /OpenCL GPUs, validating results and comparing performances for different simulations and hardware usages.

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By carefully mapping the problem onto the unique GPU architecture, we achieve order-of-magnitude speedup over a conventional CPU implementation. Furthermore, we show that the speedup is consistent across a wide range of data set sizes, making this implementation ideal for large data sets. This performance boost enables the genetic algorithm to search a larger subset of the solution space, which results in more accurate pattern classification. Finally, we demonstrate this method in the context of the 2009 UC San Diego Data Mining Contest, achieving a world-class lift on a data set of e-commerce transactions. The Weather Research and Forecasting model is a next-generation mesoscale numerical weather prediction system.

The model consists of the Master Node Dispatcher and the Worker GPU Nodes . The MND distributes the workload among the cluster working nodes and then aggregates the results. The WGN performs the multiple pair-wise sequence alignments using the Smith-Waterman algorithm. We also propose a modified implementation to the Smith-Waterman algorithm based on computing the alignment matrices row-wise. The experimental results demonstrate a considerable reduction in the running time by increasing the number of the working GPU nodes.

• It consists of a discrete particle swarm optimization and a genetic algorithm.
• The code is available in single and double precision versions, the latter compatible with FERMI architectures.
• Accepting cycle detection is the core algorithmic procedure in automata-based LTL Model Checking.
• In the past few years, co-processing on Graphics Processing Units has been a disruptive technology in High Performance Computing .
• The proposed model targets homogeneous cluster nodes equipped with similar Graphical Processing Unit cards.
• Is assessed by comparing the speed of solving three tridiagonal matrices using ADI with the speed of solving one heptadiagonal matrix using a conjugate gradient method.

We have implemented a lock-free collaborative charge-deposition algorithm for the GPU, as well as other optimizations, including local communication avoidance for GPUs, a customized FFT, and fine-tuned memory access patterns. On a small GPU cluster , our benchmarks exhibit both superior peak performance and better scaling than a CPU cluster with 16 nodes and 128 cores. We also compare the code performance on different GPU architectures, including C1070 Tesla and K20 Kepler. Programming model and they obtain speedups of orders of magnitude comparing to optimized CPU implementations. In this paper we present an implementation of a library for solving linear systems using the CCUDA framework. We present the results of performance tests and show that using GPU one can obtain speedups of about of approximately 80 times comparing with a CPU implementation.

Fortran requires a fast random number generation with good statistical properties on GPU. In this study, a GPU-based parallel pseudo random number generator have been proposed to use in high performance computing systems. According to the type of GPU memory usage, GPU scheme is divided into two work modes including GLOBAL-MODE and SHARED-MODE. To generate parallel random numbers based on the independent sequence method, the combination of middle-square method and chaotic map along with the Xorshift PRNG have been employed. Implementation of our developed PPRNG on a single GPU showed a speedup of 150x and 470x for GLOBAL-MODE and SHARED-MODE, respectively.

Performance

Implementation delivers the optimal performance predicted by our graph grammar analysis. We utilize the solver for multiple right hand sides related to the solution of non-stationary or inverse problems. We obtain speedups of 6.0 for the ADI solver on one Tesla M2050 GPU in contrast to two Xeon X5670 CPUs. Scalability tests show that our implementation can offer significant performance improvement on heterogeneous platform. The results show that one can generate at least 11 frames per second in HD (720p resolution by GPU processor and GT 840M graphic card, using trace method. If better graphic card employ, this algorithm and program can be used to generate real-time animation.

The obtained performance is compared to previous implementations utilizing the GPU through the OpenGL graphics API. We find that both performance and optimization strategies differ widely… Projecte fet en col.laboració amb Norwegian University of Science and Technology. Department of Telematics User needs increases as time passes. We started with computers like the size of a room where the perforated plaques did the same function as the current machine code object does and at present we are at a point where the number of processors within our graphic device unit it’s not enough for our requirements.

To obtain efficient implementation, we parallelized both the wrapped phase map extraction algorithm and the two-dimensional phase unwrapping algorithm. In contrast to previous implementations, we utilized unweighted least squares phase unwrapping algorithm that better suits parallelism. We compared the proposed algorithm run times on the CPU and the GPU of the computer for various sizes of off-axis holograms. We then used common-path off-axis interferometric imaging to quantitatively capture the phase maps of a micro-organism with rapid flagellum movements. Exploiting graphics processing units for computational biology and bioinformatics.

Experiments, applying different configurations, from 1 to 8 GPUs has been performed and results were compared with the sequential (non-parallel) version. A speed up of about 2.000 times has been observed when comparing the 8-GPU with the sequential version. Results here presented are discussed and analyzed with the objective of outlining gains and possible limitations of the proposed approach. And compared them with a parallel implementation of synchronous relaxation methods on CPU-based systems. For a set of test matrices taken from the University of Florida Matrix Collection we monitor the convergence behavior, the average iteration time and the total time-to-solution time. Accelerated method provides images of the same quality with a speedup factor of 318.