Optical inspection and metrology for industrial applications often require fast image processing. Today this is mostly reached by special developed hardware, which represents a relevant cost factor in image processing systems. Furthermore, such special solutions often cannot be easily adapted to new requirements. Otherwise, CPU based systems feature a good programmability but often not enough p...

In this article, the graphics processing unit (GPU)-accelerated CatBoost (GPU-CatBoost) algorithm for hyperspectral image classification is first introduced and comparatively studied using diverse features. To further foster performance from both accurate efficient viewpoints, an ensemble version of GPU-CatBoost, GPU-accelerated CatBoost-Forest (GPU-CatBF) algorithm, proposed by adopting parall...

The growing computational power of modern graphics processing units is making them very suitable for general purpose computing. These commodity processors operate generally as parallel SIMD platforms and, among other factors, the effectiveness of the codes is subject to a right exploitation of the underlying memory hierarchy. This paper deals with the implementation of the Fast Fourier Transfor...

Apart from algorithmic improvements many intensive machine learning algorithms can gain performance by parallelization. Programmable graphics processing units (GPU) offer a highly data parallel architecture that is suitable for many computational tasks in machine learning. We present an optimized k-means implementation on the graphics processing unit. NVIDIA’s Compute Unified Device Architectur...

We use a graphics processing unit (GPU) for fast calculations of helicity amplitudes of quark and gluon scattering processes in massless QCD. New HEGET (HELAS Evaluation with GPU Enhanced Technology) codes for gluon self-interactions are introduced, and a C++ program to convert the MadGraph generated FORTRAN codes into HEGET codes in CUDA (a C-platform for general purpose computing on GPU) is c...

Abell, Stephen W. MSECE, Purdue University, August 2013. Parallel Acceleration of Deadlock Detection and Avoidance Algorithms on GPUs. Major Professor: Dr. John Jaehwan Lee. Current mainstream computing systems have become increasingly complex. Most of which have Central Processing Units (CPUs) that invoke multiple threads for their computing tasks. The growing issue with these systems is resou...

Thermo vision are used in military, police custom traffic control, industrial and other specific applications for collecting and processing thermo visual information from infrared images. There is a problem in the steps of implementation of the developed methods and algorithms for infrared image processing in real time practical applications of thermo vision systems. Here is proposed to exploit...

Abstract Power electronic converter (Power Electronic Transformer, PET) is widely used in power systems, so the research on PET electromagnetic disturbance (Electro Magnetic Interference, EMI) cannot be ignored. consists of many insulated gate bipolar transistors (Insulate-Gate Bipolar Transistor, IGBT). A large number levels will cause problems such as small simulation steps and long times. To...

We present a set of algorithms for simulating and visualizing real-time crowds in GPU (Graphics Processing Units) clusters. First we present crowd simulation and rendering techniques that take advantage of single GPU machines. Then, using as an example a wandering crowd behavior simulation algorithm, we explain how this kind of algorithms can be extended for their use in GPU cluster environment...

This paper present contributions to the state-of-the art for graphics processing unit (GPU-based) embedded intelligence (EI) research architectures and applications. gives a comprehensive review representative studies of emerging current paradigms GPU-based EI with focus on architecture, technologies applications: (1) First, overview classifications are presented give full spectrum in this area...