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Keyword: Parallel Computing
Fine Tuning the Performance of Parallel Codes
We propose a multilevel method to speed highly optimized parallel codes whose runtime increases faster than their workload. This method requires the ability to solve large in- stances by decomposing them into smaller instances. Using a simple parallel computing model, we derive a mathematical model that predicts whether or not our method can im- prove…
Read More Performance Portability and Unified Profiling for Finite Element Methods on Parallel Systems
The currently available variety of modern, highly-parallel universal processors includes multi-core CPU and many-core GPU (Graphics Processing Units) from different vendors. Systems composed of such processors enable high-performance execution of demanding applications like numerical Finite Element Methods. However, today’s application pro- gramming for parallel systems lacks performance portability: the same program code cannot achieve stable…
Read More Automatic Stochastic Dithering Techniques on GPU: Image Quality and Processing Time Improved
Dithering or error diffusion is a technique used to obtain a binary image, suitable for printing, from a grayscale one. At each step, the algorithm computes an allowed value of a pixel from a grayscale one, applying a threshold and, therefore, causing a conversion error. To obtain the optical illusion of a continuous tone, the…
Read More A novel model for Time-Series Data Clustering Based on piecewise SVD and BIRCH for Stock Data Analysis on Hadoop Platform
With the rapid growth of financial markets, analyzers are paying more attention on predictions. Stock data are time series data, with huge amounts. Feasible solution for handling the increasing amount of data is to use a cluster for parallel processing, and Hadoop parallel computing platform is a typical representative. There are various statistical models for…
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