scholarly journals A NewSpeed Power Area and Accuracy (SPAA) Aware Cordic Processing Unit By Vedic Mathematics For The Application of Computer Vision

2021 ◽  
Vol 12 (2) ◽  
pp. 3199-3209
Author(s):  
Nitesh Kumar Sharma, Et. al.
Keyword(s):  
Computer Vision ◽  
High Speed ◽  
Graphics Processing Unit ◽  
Processing Unit ◽  
Arithmetic Unit ◽  
Vedic Mathematics ◽  
Fast Processing ◽  
Calculation Processing ◽  
Graphics Processing ◽  
The Brain

we are living in the era of fast processing applications like 3D, 5G, 9D. These types of application need a processing unit which have separate arithmetic unit & separate trigonometric unit which is well known as CORDIC processing unit. As we know Graphics processing unit is the brain of any graphics systems now a days there is Gaming specific systems are available which require ultra-high-speed GPU on those GPU there is separate trigonometric calculation processing unit is there which is called CORDIC. So, in this paper basically we proposed a novel architecture of CORDIC unit which is able to give the output in very less time. In this paper we also try to do the justice with the speed power area and accuracy Metrix.

IMAGE REGISTRATION AND FUSION SYSTEM BASED ON GPU

2010 ◽  
Vol 19 (01) ◽  
pp. 173-189
Author(s):  
SEUNG-HUN YOO ◽  
CHANG-SUNG JEONG
Keyword(s):  
Visual Information ◽  
High Speed ◽  
Graphics Processing Unit ◽  
Aerial Images ◽  
Processing Unit ◽  
Infrared Sensors ◽  
Fusion Algorithm ◽  
Registration Method ◽  
Multi Scale ◽  
Graphics Processing

Graphics processing unit (GPU) has surfaced as a high-quality platform for computer vision-related systems. In this paper, we propose a straightforward system consisting of a registration and a fusion method over GPU, which generates good results at high speed, compared to non-GPU-based systems. Our GPU-accelerated system utilizes existing methods through converting the methods into the GPU-based platform. The registration method uses point correspondences to find a registering transformation estimated with the incremental parameters in a coarse-to-fine way, while the fusion algorithm uses multi-scale methods to fuse the results from the registration stage. We evaluate performance with the same methods that are executed over both CPU-only and GPU-mounted environment. The experiment results present convincing evidences of the efficiency of our system, which is tested on a few pairs of aerial images taken by electro-optical and infrared sensors to provide visual information of a scene for environmental observatories.

scholarly journals A REVIEW ON IMAGE SEGMENTATION USING GPU

2016 ◽  
Vol 15 (10) ◽  
pp. 7160-7163
Author(s):  
Gurpreet Kaur ◽  
Sonika Jindal
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Image Segmentation ◽  
Graphics Processing Unit ◽  
Processing Unit ◽  
System Resources ◽  
Cuda Architecture ◽  
Graphics Processing

Image Segmentations play a heavy role in areas such as computer vision and image processing due to its broad usage and immense applications. Because of the large importance of image segmentation a number of algorithms have been proposed and different approaches have been adopted. Segmentation divides an image into distinct regions containing each pixel with similar attributes. The objective of apportioning is to simplify and/or alter the representation of an image into something that is more meaningful and more comfortable to break down. This paper discusses the various techniques implemented for image segmentation and discusses the various Computations that can be performed on the graphics processing unit (GPU) by means of the CUDA architecture in order to achieve fast performance and increase the utilization of available system resources.

scholarly journals Parallelized multi–graphics processing unit framework for high-speed Gabor-domain optical coherence microscopy

2014 ◽  
Vol 19 (7) ◽  
pp. 071410 ◽  
Author(s):  
Patrice Tankam ◽  
Anand P. Santhanam ◽  
Kye-Sung Lee ◽  
Jungeun Won ◽  
Cristina Canavesi ◽  
...  
Keyword(s):  
High Speed ◽  
Graphics Processing Unit ◽  
Processing Unit ◽  
Optical Coherence ◽  
Optical Coherence Microscopy ◽  
Gabor Domain ◽  
Graphics Processing

High-speed feedback control of an oscillating magnetic helicity injector using a graphics processing unit

2021 ◽  
Vol 92 (5) ◽  
pp. 053530
Author(s):  
K. D. Morgan ◽  
A. C. Hossack ◽  
C. J. Hansen ◽  
B. A. Nelson ◽  
D. A. Sutherland
Keyword(s):  
Feedback Control ◽  
High Speed ◽  
Graphics Processing Unit ◽  
Magnetic Helicity ◽  
Processing Unit ◽  
Graphics Processing

Accelerating IP routing algorithm using graphics processing unit for high speed multimedia communication

2014 ◽  
Vol 75 (23) ◽  
pp. 15365-15379 ◽  
Author(s):  
Jia Uddin ◽  
In-Kyu Jeong ◽  
Myeongsu Kang ◽  
Cheol-Hong Kim ◽  
Jong-Myon Kim
Keyword(s):  
High Speed ◽  
Graphics Processing Unit ◽  
Routing Algorithm ◽  
Multimedia Communication ◽  
Processing Unit ◽  
Ip Routing ◽  
Graphics Processing

Seafloor Pressure Signatures of a High-Speed Boat in Shallow Water With SPH

2014 ◽  
Author(s):  
Angelantonio Tafuni ◽  
Iskender Sahin
Keyword(s):  
Shallow Water ◽  
High Speed ◽  
Graphics Processing Unit ◽  
Processing Unit ◽  
Computational Domain ◽  
Particle Hydrodynamics ◽  
Smoothed Particle ◽  
Good Trade ◽  
Seafloor Pressure ◽  
Graphics Processing

Smoothed Particle Hydrodynamics (SPH) based simulations are implemented to evaluate the pressure-induced signatures on the ocean floor due to the passage of a high-speed boat in quiescent shallow water. Along with the standard Weakly-Compressible SPH (WCSPH) equations, the delta-SPH formulation is employed, which modifies the SPH continuity equation by incorporating numerical diffusion. This correction allows for a considerable reduction of the spurious oscillations characterizing pressure fields obtained with WCSPH algorithms. A simple computer model of a planing boat is developed for comparison with similar works in the literature. Simulations are performed using a parallel open-source SPH code on a high-end graphics processing unit (GPU). A convergence study on the size of the optimal computational domain is carried out, with a total number of particles per simulation ranging between 100,000 to 20,000,000. Part of the computational work is directed towards the investigation of the best set of SPH parameters to be employed in this specific study, with particular attention to the choice of a suitable kernel function, particle resolution and viscosity coefficients. Pressure contours and pressure plots at lateral locations at the seafloor are presented, showing good agreement with previous studies. It can be inferred that the SPH methodology is a suitable choice for free-surface problems, offering a good trade-off among the ease of implementation, computational efficiency and accuracy of the results.

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