This paper introduces a reaction-diffusion-chemotaxis model for bacterial aggregation patterns on the surface of thin agar plates. It is based on the non-linear degenerate cross diffusion model proposed by Kawasaki et al. [1] and it includes a suitable nutrient chemotactic term compatible with such type of diffusion. High resolution numerical simulations using Graphic Processing Units (GPUs) of...

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...

Feature or variable selection still remains an unsolved problem, due to the infeasible evaluation of all the solution space. Several algorithms based on heuristics have been proposed so far with successful results. However, these algorithms were not designed for considering very large datasets, making their execution impossible, due to the memory and time limitations. This paper presents an imp...

The fundamental drawback of current stereo and multi-view display techniques is the necessity to perform multi-pass rendering (one pass for each separate view) and subsequent image composition-andmasking for generating multi-stereo views. Thus the rendering time increases in general linearly with the number of rendered views. An increase in frame-rate can be achieved by sub-resolution rendering...

In this paper, a fast and practical GPU-based implementation of Fuzzy C-Means (FCM) clustering algorithm for image segmentation is proposed. First, an extensive analysis is conducted to study the dependency among the image pixels in the algorithm for parallelization. The proposed GPU-based FCM has been tested on digital brain simulated dataset to segment white matter(WM), gray matter(GM) and ce...

We present a portable platform, called PIC ENGINE, for accelerating Particle-In-Cell (PIC) codes on heterogeneous many-core architectures such as Graphic Processing Units (GPUs). The aim of this development is efficient simulations on future exascale systems by allowing different parallelization strategies depending on the application problem and the specific architecture. To this end, this pla...

This work proposes an energy-efficient hardware accelerated Linear Programming (LP) solver. The system is based on the Simplex Algorithm for solving LP problems and is operable on Field Programmable Gate Arrays (FPGAs), Graphic Processing Units (GPUs), and Multi-Core Computer Processors (CPUs). The system is targeted towards the dense problems in radiotherapy applications as they represent a ch...

We propose a progressive radiance estimation engine (PREE) hardware architecture to accelerate the processing of the progressive photon mapping with satisfactory graphic quality. The presented PREE architecture consists of four progressive radiance estimation units (PREUs), approximate full task schedule-oriented hit-point update operation controller (AFTSO-HpUOC) and approximate data-independe...

The 3DCGiRAM is a 3D-graphic accelerator designed for photo-realistic image synthesis. The 3DCGiRAM is equipped with graphics processing units that perform ray-object intersection calculations and intensity calculations for rays traced over a 3D virtual object space. It also has a hardwareaccelerated 3D line generator, which effectively finds objects in a grid space that are likely to intersect...

19 In general, pattern recognition techniques require a high computational burden for learning the discriminating functions that are responsible to separate samples from distinct classes. As such, there are several studies that make effort to employ machine learning algorithms in the context of “big data” classification problems. The research on this area ranges from Graphics Processing Units-b...