Posts
Mar, 5
Accelerating Simulation of Agent-Based Models on Heterogeneous Architectures
The wide usage of GPGPU programming models and compiler techniques enables the optimization of data-parallel programs on commodity GPUs. However, mapping GPGPU applications running on discrete parts to emerging integrated heterogeneous architectures such as the AMD Fusion APU and Intel Sandy/Ivy bridge with the CPU and the GPU on the same die has not been […]
Mar, 5
Parallel Ray Tracing in Scientific Visualization
Ray tracing presents an efficient rendering algorithm for scientific visualization using common visualization tools and scales with increasingly large geometry counts while allowing for accurate physically-based visualization and analysis, which enables enhanced rendering and new visualization techniques. Interactivity is of great importance for data exploration and analysis in order to gain insight into large-scale data. […]
Mar, 5
Parallel Algorithm for Generation of Test Recommended Path using CUDA
Software testing of an application makes the user to find defect. The users, called testers, should test the various situations with test cases. In order to make test cases, many states and events have to be considered. It takes much time to create test cases with many states and events. Instead of using the common […]
Mar, 5
Performance Analysis of a Symmetric Cryptographic Algorithm on Multicore Architectures
In this paper, a performance analysis of the symmetric encryption algorithm AES (Advanced Encryption Standard) on various multicore architectures is presented. To this end, three implementations based on C language that use the parallel programming tools OpenMP, MPI and CUDA to be run on multicore processors, multicore clusters and GPU, respectively, were carried out. The […]
Mar, 5
Large-scale Virtual Acoustics Simulation at Audio Rates Using Three Dimensional Finite Difference Time Domain and Multiple GPUs
The computation of large-scale virtual acoustics using the 3D finite difference time domain (FDTD) is prohibitively computationally expensive, especially at high audio sample rates, when using traditional CPUs. In recent years the computer gaming industry has driven the development of extremely powerful Graphics Processing Units (GPUs). Through specialised development and tuning we can exploit the […]
Mar, 3
Low-Energy Application Parallelism 2013, LEAP 2013
LEAP 2013 is the place to learn about and share the latest advances in the use of high-performance parallel computing technology on low-power mobile CPU, GPU, FPGA and embedded processors. Two days of world-class education and networking will give developers, researchers, engineers and technology managers the vital knowledge they need to understand, assess and exploit […]
Mar, 2
OpenOF: Framework for Sparse Non-linear Least Squares Optimization on a GPU
In the area of computer vision and robotics non-linear optimization methods have become an important tool. For instance, all structure from motion approaches apply optimizations such as bundle adjustment (BA). Most often, the structure of the problem is sparse regarding the functional relations of parameters and measurements. The sparsity of the system has to be […]
Mar, 2
Accelerating Kernel Density Estimation on the GPU Using the CUDA Framework
The main problem of the kernel density estimation methods is the huge computational requirements, especially for large data sets. One way for accelerating these methods is to use the parallel processing. Recent advances in parallel processing have focused on the use Graphics Processing Units (GPUs) using Compute Unified Device Architecture (CUDA) programming model. In this […]
Mar, 2
Efficient Detection of Sunspots with GPU Acceleration Through CUDA
Tracking sunspots is not an easy task given that multiple sources of data are acquired using a variety of different instruments. With the sources of data and contributors to this repositories quickly growing, it is increasingly important to have an efficient solution to analyze the photographs to record trends and possibly make predictions. CUDA (Compute […]
Mar, 2
Full Covariance Gaussian Mixture Models Evaluation on GPU
Gaussian mixture models (GMMs) are often used in various data processing and classification tasks to model a continuous probability density in a multi-dimensional space. In cases, where the dimension of the feature space is relatively high (e.g. in the automatic speech recognition (ASR)), GMM with a higher number of Gaussians with diagonal covariances (DC) instead […]
Mar, 2
On Performance of GPU and DSP Architectures for Computationally Intensive Applications
This thesis focuses on the implementations of a support vector machine (SVM) algorithm on digital signal processor (DSP), graphics processor unit (GPU), and a common Intel i7 core architecture. The purpose of this work is to identify which of the three is most suitable for SVM implementation. The performance is measured by looking at the […]
Mar, 2
Large-scale ferrofluid simulations on graphics processing units
We present an approach to molecular-dynamics simulations of ferrofluids on graphics processing units (GPUs). Our numerical scheme is based on a GPU-oriented modification of the Barnes-Hut (BH) algorithm designed to increase the parallelism of computations. For an ensemble consisting of a million ferromagnetic particles, the performance of the proposed algorithm on a Tesla M2050 GPU […]
