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Showing 1 to 20 of 38 for “"GPU computing"”.
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The case for reconfigurable general purpose GPU computing
General purpose graphics processing unit (GPU) computing (GPGPU) has emerged as a new paradigm for programmers to exploit massive amounts of parallelism for relatively low costs. The abundance of GPUs in desktop and mobile computing platforms makes them ideal for accelerating tasks on multiple …
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Movement and placement of non-contiguous data in distributed GPU computing
… are the first comprehensive evaluation of all GPU communication primitives. For communication-heavy applications, optimally using communication capabilities is challenging and essential for performance. Two different approaches are examined. The first is a high-level 3D stencil communication …
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Directive-Based Data Partitioning and Pipelining and Auto-Tuning for High-Performance GPU Computing
… accelerators, such as graphics processing units (GPUs), field-programmable gate arrays (FPGAs), and co-processors (e.g., Intel Xeon Phi), due to their increasing use in state-of-the-art supercomputers. Over the past 10 years, we have seen a significant improvement in both computing power and …
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Physical modeling and high-performance GPU computing for characterization, interception, and disruption of hazardous near-Earth objects
… is done by applying ideas in high-performance computing (HPC) on the computer graphics processing unit (GPU). Rather than prove a concept through large standalone simulations on a supercomputer, a highly parallel structure allows for flexible, target dependent questions to be resolved. Built …
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OpenMP-CUDA implementation of the moment method and multilevel fast multipole algorithm on multi-GPU computing systems
… multipole algorithm (MLFMA) are implemented for GPU computation based on the hybrid OpenMP-CUDA parallel programming model. The resultant algorithms are called the OpenMP-CUDA-MoM and the OpenMP-CUDA-MLFMA, respectively. Both of the proposed methods are applied to compute electromagnetic …
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Multi-drug association rule mining on graphics processing unit
… and symptoms to be discovered. General-purpose GPU computing is the next evolution in processing architectures; utilization of this massively parallel processor towards drug data mining will accelerate the research and discovery of drug-symptom associations that will save money and lives"--Leaf …
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Millipyde: A Cross-Platform Python Framework for Transparent GPU Acceleration
<p>The prevalence of general-purpose GPU computing continues to grow and tackle a wider variety of problems that benefit from GPU-acceleration. This acceleration often suffers from a high barrier to entry, however, due to the complexity of software tools that closely map to the underlying GPU …
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Computation in Macroeconomic Asset Pricing
… the wide applicability and potential gains of GPU computing, a parallel computing framework, and applies those tools to a computationally challenging model which investigates trading volume in a general equilibrium, complete-markets economy where agents have heterogeneous beliefs.</p>
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GPU-Oriented Algorithms for Continuous Energy Monte Carlo Neutron Transport
The advent of graphics processing units (GPUs) has brought computing to new heights with deep learning models, now deployed ubiquitously and touching the lives of many. While GPU hardware may be ideal for deep learning, its full potential in various scientific computing applications has yet to be …
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GPU ray tracing with CUDA
… methods. Fortunately, technological advances in GPU computing have provided the means to accelerate the ray tracing process to produce images in a significantly shorter time. This paper attempts to clearly illustrate the difference in rendering speed and design by developing and comparing a …
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A Multi-GPU Compute Solution for Optimized Genomic Selection Analysis
… themselves nicely to standard high performance computing optimizations such as parallelism, while others do not. One such algorithm is Markov Chain Monte Carlo (MCMC). In this thesis, we present a heterogeneous compute solution for optimizing GenSel, a genetic selection analysis tool. GenSel …
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Multi-GPU Load Balancing for Simulation and Rendering
GPU computing can significantly improve performance by taking advantage of massive parallelism of GPUs for data parallel applications. Computation in visualization applications is suitable for parallelization on the GPU, which can improve performance and interactivity in these applications. If used …
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Multi-level Parallelism with MPI and OpenACC for CFD Applications
… abstracts the details of implementation on the GPU. Although OpenACC generally limits the performance of the GPU, this model significantly reduces the work required to port an existing code to any accelerator platform, including GPUs. The purpose of this research is twofold: to investigate the …
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GPU-based, Microsecond Latency, Hecto-Channel MIMO Feedback Control of Magnetically Confined Plasmas
… first time, employs a Graphics Processing Unit (GPU) for microsecond-latency, real-time control computations. This novel application area for GPU computing is opened up by a new system architecture that is optimized for low-latency computations on less than kilobyte sized data samples as they …
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GPU Integration into a Software Defined Radio Framework
… as possible. Graphics Processing Units (GPUs) designed years ago for video rendering, are now finding new uses in research. The parallel architecture provided by the GPU gives developers the ability to speed up the performance of computationally intense programs. An open source tool for …
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Using hybrid shared and distributed caching for mixed-coherency GPU workloads
Current GPU computing models support a mixture of coherent and incoherent classes of memory operations. Workloads using these models typically have working sets too large to fit in an economical SRAM structure. Still, GPU architectures have last-level caches to primarily fulfill two functions: …
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Lattice Boltzmann liquid simulations on graphics hardware
… general purpose Graphics Processing Unit (GPU) computing has potential as a relatively inexpensive way to reduce these simulation times. In recent years, GPUs have been used to achieve enormous speedups via their massively parallel architectures. Within the field of fluid simulation, the …
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Interactive simulation and rendering of fluids on graphics hardware
… media. However, using the massive parallelism of GPUs, it is nowadays possible to produce uid visual effects in real time for interactive applications such as games. We present such an interactive simulation using the CUDA GPU computing environment and OpenGL graphics API. Smoothed Particle …
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GPU-enhanced power flow analysis
… the utilization of Graphics Processing Units (GPUs) to improve the Power Flow (PF) analysis of modern power systems. GPUs are powerful vector co-processors that have been very useful in the acceleration of several computational intensive applications. PF analysis is the steady-state analysis of …
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Modified nodal integral method for Navier-Stokes equations incorporated with generic quadrilateral elements, and GPU-based parallel computing
… domains, on graphics processing units (GPUs). Nodal methods have become the backbone and workhorse of the core design production codes used in the nuclear industry for decades. As a variation of the coarse mesh nodal methods, the modified nodal integral method can accurately solve the …
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