نتایج جستجو برای: بستر cuda

تعداد نتایج: 19735  

2012
Alberto Ferreira de Souza Lucas de Paula Veronese Leonardo M. Lima Claudine Badue Lucia Catabriga

We analyze two parallel finite element implementations of the 2D time-dependent advection diffusion problem, one for multi-core clusters and one for CUDA-enabled GPUs, and compare their performances in terms of time and energy consumption. The parallel CUDA-enabled GPU implementation was derived from the multi-core cluster version. Our experimental results show that a desktop machine with a sin...

Journal: :Italian Journal of Science & Engineering 2017

2008
Sain-Zee Ueng Melvin Lathara Sara S. Baghsorkhi Wen-mei W. Hwu

Abstract. The computer industry has transitioned into multi-core and many-core parallel systems. The CUDA programming environment from NVIDIA is an attempt to make programming many-core GPUs more accessible to programmers. However, there are still many burdens placed upon the programmer to maximize performance when using CUDA. One such burden is dealing with the complex memory hierarchy. Effici...

2012
Veysel Demir Atef Z. Elsherbeni

─ In this contribution, a compute unified device architecture (CUDA) implementation of a two-dimensional finite-difference time-domain (FDTD) program is presented along with the OpenGL interoperability to visualize electromagnetic fields as an animation while an FDTD simulation is running. CUDA, which runs on a graphics processing unit (GPU) card, is used for electromagnetic field data generati...

Journal: :CoRR 2013
Bogdan Oancea Tudorel Andrei Raluca Mariana Dragoescu

Since the first idea of using GPU to general purpose computing, things have evolved over the years and now there are several approaches to GPU programming. GPU computing practically began with the introduction of CUDA (Compute Unified Device Architecture) by NVIDIA and Stream by AMD. These are APIs designed by the GPU vendors to be used together with the hardware that they provide. A new emergi...

Journal: :Computer Physics Communications 2011
Chao-Tung Yang Chih-Lin Huang Cheng-Fang Lin

a r t i c l e i n f o a b s t r a c t Nowadays, NVIDIA's CUDA is a general purpose scalable parallel programming model for writing highly parallel applications. It provides several key abstractions – a hierarchy of thread blocks, shared memory, and barrier synchronization. This model has proven quite successful at programming multithreaded many core GPUs and scales transparently to hundreds of ...

2012
Pedro D. Bello Yuanwei Jin Enyue Lu

This paper develops implementation strategy and method to accelerate the propagation and backpropagation (PBP) tomographic imaging algorithm using Graphic Processing Units (GPUs). The Compute Unified Device Architecture (CUDA) programming model is used to develop our parallelized algorithm since the CUDA model allows the user to interact with the GPU resources more efficiently than traditional ...

2012
PRITAM PRAKASH S. K. BOSE

We propose and implement a pyramidal image blending algorithm using modern programmable graphic processing units. This algorithm is an essential part of an image stitching process for a seamless panoramic mosaic. The CUDA framework is a novel GPU programming framework from NVIDIA. We realize significant acceleration in computations of the pyramidal image blending algorithm by utilizing the CUDA...

2015
Changbo Chen Xiaohui Chen Abdoul-Kader Keita Marc Moreno Maza Ning Xie

In this paper, we present the accelerator model of MetaFork together with the software framework that allows automatic generation of CUDA code from annotated MetaFork programs. One of the key features of this CUDA code generator is that it supports the generation of CUDA kernel code where program parameters (like number of threads per block) and machine parameters (like shared memory size) are ...

Journal: :Advanced Computing: An International Journal 2012

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