Radio propagation simulation tools are important for prediction and verification of the radio signal coverage by individual transmitters or transmitter networks such as mobile phone cellular networks. In the case of a large geographic area with a relative high resolution, the simulation can become computationally demanding, taking a considerable amount of time to accomplish. Parallel processing...

This paper deals with GPU computing of special mathematical functions that are used in Fractional Calculus. The graphics processing unit (GPU) has grown to be an integral part nowadays’s mainstream structures. a novel parallel approach for NVIDIA’s hardware is speed up the algorithm. A comparison sequential code, vectorized code and performed. We have successfully reduced computation time using...

We present a fast, accurate and robust parallel Levenberg-Marquardt minimization optimizer, GPU-LMFit, which is implemented on graphics processing unit for high performance scalable parallel model fitting processing. GPU-LMFit can provide a dramatic speed-up in massive model fitting analyses to enable real-time automated pixel-wise parametric imaging microscopy. We demonstrate the performance o...

Image segmentation is one of the most common steps in digital image processing. The area many image segmentation algorithms (e.g., thresholding, edge detection, and region growing) employed for classifying a digital image into different segments. In this connection, finding a suitable algorithm for medical image segmentation is a challenging task due to mainly the noise, low contrast, and steep...

The exceptional growth of graphics hardware in programmability and data processing speed in the past few years has fuelled extensive research in using it for general purpose computations more than just image-processing and gaming applications. We explore the use of graphics processors (GPU) to speedup the computations involved in Fuzzy c-means (FCM). FCM is an important iterative clustering alg...

Graphics processing unit (GPUs) are used in wide range of application now a days particularly Medical image processing in GPU becomes popular recently. Medical imaging procedures are often computationally demanding due to three dimensional data sets. With enhancing performances of graphic processors, improved programming support, GPU has emerged as a competitive parallel computing platform for ...

The Graphics Processing Unit (GPU) is now commonly used for graphics and data-parallel computing. As more and more applications tend to accelerate on the GPU in multi-tasking environments where multiple tasks access the GPU concurrently, operating systems must provide prioritization and isolation capabilities in GPU resource management, particularly in real-time setups. We present TimeGraph, a ...

This paper presents a massively parallel Genetic Algorithm – Pattern Search (GA-PS) with graphics hardware acceleration on bound constrained nonlinear optimization problems. The objective of this study is to determine the effectiveness of using Graphics Processing Units (GPU) as a hardware platform for Genetic Algorithms (GA). The global search of the GA is enhanced by a local Pattern Search (P...

Thanks to their high performance and programmability, the latest graphics cards can now be used for scientific purpose. They are indeed very efficient parallel Single Instruction Multiple Data (SIMD) machines. This new trend is called General Purpose computation on Graphics Processing Unit (GPGPU [13]). Regarding the stereo problem, variational methods based on deformable models provide dense, ...