Posts
May, 19
Use of FPGA or GPU-based architectures for remotely sensed hyperspectral image processing
Hyperspectral imaging is a growing area in remote sensing in which an imaging spectrometer collects hundreds of images (at different wavelength channels) for the same area on the surface of the Earth. Hyperspectral images are extremely high-dimensional, and require advanced on-board processing algorithms able to satisfy near real-time constraints in applications such as wildland fire […]
May, 16
An Introduction to the OpenCL Programming Model
This paper presents an overview of the OpenCL 1.1 standard [Khronos 2012]. We first motivate the need for GPGPU computing and then discuss the various concepts and technological background necessary to understand the programming model. We use concurrent matrix multiplication as a framework for explaining various performance characteristics of compiling and running OpenCL code, and […]
May, 16
GPU accelerated Nonlinear Soft Tissue Deformation
There are two types of structures in human body, solid organs and hollow membrane like organs. Brain, liver and other soft tissues such as tendons, muscles, cartilage etc., are examples of solid organs. Colon and blood vessels are examples of hollow organs. They greatly differ in structure and mechanical behavior. Deformation of these types of […]
May, 16
Accelerated Network Coding with Dynamic Stream Decomposition on Graphics Processing Unit
Network coding, a well-known technique for optimizing data-flow in wired and wireless network systems, has attracted considerable attention in various fields. However, the decoding complexity in network coding becomes a major performance bottleneck in the practical network systems; thus, several researches have been conducted for improving the decoding performance in network coding. Nevertheless, previously proposed […]
May, 16
b-Bit Minwise Hashing in Practice: Large-Scale Batch and Online Learning and Using GPUs for Fast Preprocessing with Simple Hash Functions
In this paper, we study several critical issues which must be tackled before one can apply b-bit minwise hashing to the volumes of data often used industrial applications, especially in the context of search. 1. (b-bit) Minwise hashing requires an expensive preprocessing step that computes k (e.g., 500) minimal values after applying the corresponding permutations […]
May, 16
A Heterogeneous Accelerated Matrix Multiplication: OpenCL + APU + GPU+ Fast Matrix Multiply
As users and developers, we are witnessing the opening of a new computing scenario: the introduction of hybrid processors into a single die, such as an accelerated processing unit (APU) processor, and the plug-and-play of additional graphics processing units (GPUs) onto a single motherboard. These APU processors provide multiple symmetric cores with their memory hierarchies […]
May, 15
The BiConjugate gradient method on GPUs
In a wide variety of applications from different scientific and engineering fields, the solution of complex and/or nonsymmetric linear systems of equations is required. To solve this kind of linear systems the BiConjugate Gradient method (BCG) is especially relevant. Nevertheless, BCG has a enormous computational cost. GPU computing is useful for accelerating this kind of […]
May, 15
Batch Records Insertion into Multidimensional Linear Dynamic Hashing Table on GPU
Many parallel indexing solutions of multidimensional data have been proposed on graphics processing units (GPU) platform, whereas none of them has considered the dynamic update of data. A new solution of inserting batch records into multidimensional linear dynamic hashing (MLDH) table has been presented in this paper, which has implemented lock-free batch insertion and update […]
May, 15
Fast Adaptive Sampling Technique for Multi-Dimensional Integral Estimation Using GPUs
Evaluating multi-dimensional integrals is a commonly encountered problem in many areas of science including Physics and Volume estimation of convex bodies. One of the widely used techniques for integral evaluation in large dimensions is the Monte Carlo method. Vanilla Monte Carlo methods of Integral Estimation use uniform sampling techniques. Variance of such uniform sampling reduces […]
May, 15
Parallel implementation of a ray tracer for underwater sound waves using the cuda libraries: description and application to the simulation of underwater networks
One of the most time-consuming parts of the simulation of underwater networks is the realistic simulation of underwater sound propagation. Some well-known software tools used for networks simulations to date employ ray tracing to simulate sound propagation. This gives rise to high computational complexity, and may require very long time to complete a simulation. In […]
May, 15
A Monte Carlo Neutron Transport Code for Eigenvalue Calculations on a Dual-GPU System and CUDA Environment
Monte Carlo (MC) method is able to accurately calculate eigenvalues in reactor analysis. Its lengthy computation time can be reduced by general-purpose computing on Graphics Processing Units (GPU), one of the latest parallel computing techniques under development. The method of porting a regular transport code to GPU is usually very straightforward due to the "embarrassingly […]
May, 15
An Automatic Speech Recognition Application Framework for Highly Parallel Implementations on the GPU
Data layout, data placement, and synchronization processes are not usually part of a speech application expert’s daily concerns. Yet failure to carefully take these concerns into account in a highly parallel implementation on the graphics processing units (GPUs) could mean an order of magnitude of loss in application performance. In this paper we present an […]
