Results 151 to 160 of about 401,991 (182)

On GPU’s viability as a middleware accelerator

Cluster Computing, 2009
Today Graphics Processing Units (GPUs) are a largely underexploited resource on existing desktops and a possible cost-effective enhancement to high-performance systems. To date, most applications that exploit GPUs are specialized scientific applications.
Samer Al-Kiswany, Abdullah Gharaibeh, Elizeu Santos-Neto, Matei Ripeanu   +3 more
openaire   +1 more source

GPU-accelerated path rendering

ACM Transactions on Graphics, 2012
For thirty years, resolution-independent 2D standards (e.g. PostScript, SVG) have depended on CPU-based algorithms for the filling and stroking of paths. Advances in graphics hardware have largely ignored accelerating resolution-independent 2D graphics rendered from paths.
Mark J. Kilgard, Jeff Bolz
openaire   +1 more source

GPU-accelerated charge mapping

2016 IEEE High Performance Extreme Computing Conference (HPEC), 2016
Charge Mapping is critical to electrostatics computations such as performed in Molecular Dynamics simulations. It reduces the complexity of evaluating long-range Coulombic forces by diffusing discrete particle charges onto a regular grid. Acceleration of this stage using GPUs is non-trivial, with the compute and memory intensive nature of the algorithm
Ahmed Sanaullah, Saiful A. Mojumder, Kathleen M. Lewis, Martin C. Herbordt   +3 more
openaire   +1 more source

Accelerating financial applications on the GPU

Proceedings of the 6th Workshop on General Purpose Processor Using Graphics Processing Units, 2013
The QuantLib library is a popular library used for many areas of computational finance. In this work, the parallel processing power of the GPU is used to accelerate QuantLib financial applications. Black-Scholes, Monte-Carlo, Bonds, and Repo code paths in QuantLib are accelerated using hand-written CUDA and OpenCL codes specifically targeted for the ...
Scott Grauer-Gray, William Killian, Robert Searles, John Cavazos   +3 more
openaire   +2 more sources

Accelerating continuous GRASP with a GPU

The Journal of Supercomputing, 2019
This work proposes a GPU-based parallelization for the Continuous GRASP (C-GRASP), a local search metaheuristic for finding cost-efficient solutions to continuous global optimization problems subject to box constraints. C-GRASP has demonstrated competitive performance on several well-known multimodal test functions as well as on difficult real-world ...
Bruno C. S. Nogueira, Eduardo Tavares, Jean Araujo 0001, Gustavo Callou   +3 more
openaire   +2 more sources

Acceleration Techniques for FETI Solvers for GPU Accelerators

2018 International Conference on High Performance Computing & Simulation (HPCS), 2018
In this paper we evaluate several approaches to performing simultaneous matrix-vector multiplication of large numbers of matrices on a GPU accelerator. The goal of this evaluation is to develop efficient techniques for massively parallel Hybrid Total FETI solvers in our ESPRESO library. FETI solvers generally use sparse matrices.
Radim Vavrík, Lubomir Riha
openaire   +2 more sources

Accelerating sparse Cholesky factorization on GPUs

Parallel Computing, 2014
Sparse direct factorization is a critical component of scientific computingGPU acceleration of it is difficult due to algorithmic irregularity and PCIe perf.We present an algorithm for GPU acceleration which resolves these issues.The algorithm shows 2x speedup vs.
Steven C. Rennich, Darko Stosic, Timothy A. Davis 0001   +2 more
openaire   +1 more source

Accelerating Visual Categorization with the GPU

2012
Visual categorization is important to manage large collections of digital images and video, where textual meta-data is often incomplete or simply unavailable. The bag-of-words model has become the most powerful method for visual categorization of images and video. Despite its high accuracy, a severe drawback of this model is its high computational cost.
Koen E. A. van de Sande, Theo Gevers, Cees G. M. Snoek   +2 more
openaire   +2 more sources

GPU acceleration of numerical weather prediction

2008 IEEE International Symposium on Parallel and Distributed Processing, 2008
Weather and climate prediction software has enjoyed the benefits of exponentially increasing processor power for almost 50 years. Even with the advent of large-scale parallelism in weather models, much of the performance increase has come from increasing processor speed rather than increased parallelism. This free ride is nearly over.
John Michalakes, Manish Vachharajani
openaire   +2 more sources

Accelerating RTL simulation with GPUs

2011 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2011
Hao Qian 0001, Yangdong Deng
openaire   +1 more source