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A major component of many advanced programming courses is an open-ended "end-of-term project" assignment. Delivering and evaluating open-ended parallel programming projects for hundreds or thousands of students brings a need for broad system reconfigurability coupled with challenges of testing and development uniformity, access to esoteric hardware and programming environments, scalability,...
Hypertensive Retinopathy (HR) cause serious damage to human body if not diagnosed early. Therefore, the early diagnosis of this anomaly is very important and complicated process. The most prominent aspect of HR is that the thickness of the blood vessels on the retina change. This change can be calculated with Arteriovenous ratio (AVR). Just before AVR calculation, the veins must be found and extracted...
In this study, Sparsity-driven Change Detection (SDCD) method, which has been proposed for detecting changes in multitemporal synthetic aperture radar (SAR) images, is parallelized to reduce the execution time. Parallelization of the SDCD is realized using OpenMP on CPU and CUDA on GPU. Execution speed of the parallelized SDCD is shown on real-world SAR images. Our experimental results show that the...
Computational genomics refers to the use of numerical and statistical analysis to extract data from genetic materials in organisms. In recent years, studies in bioinformatics have focused on understanding genomes and their functions using genome sequences. The huge demand for low-cost sequencing forces the development of high-efficiency sequencing technologies. One of these is the Next-Generation...
Background Subtraction is the major important step in many image processing applications which can be applied in much of video surveillances. The major result of this method is accuracy as well as processing time. So we mainly focused on these two challenges. We parallelized the Two Layered CodeBook Model on Graphical Processing Unit (GPU) for increasing the processing speed and the accuracy of the...
To solve the problems associated with large data volume real-time processing, heterogeneous systems using various computing devices are increasingly used. The characteristic of solving this class of problems is related to the fact that there are two directions for improving methods of real-time data analysis: the first is the development of algorithms and approaches to analysis, and the second is...
An algorithm for simulating the particle population balance in case of breakage is designed to function on a Graphic Processing Unit (GPU) in a Compute Unified Device Architecture (CUDA). The GPU lowers the computational cost of the particle breakage simulation, which is generally complex and demanding. We simulate particle breakage by a Population Balance-Monte Carlo (PB-MC) simulation method. Data...
String matching problems such as sequence alignment is one of the fundamental problems in many computer since fields such as natural language processing (NLP) and bioinformatics. Many algorithms have been proposed in the literature to address this problem. Some of these algorithms compute the edit distance between the two strings to perform the matching. However, these algorithms usually require long...
Aiming at the problem for the online real-time detection of fabric defect, this paper uses the method of Fast Fourier Transform based on CUDA to detect the fabric defect, This method adopts multi thread parallel implementation of FFT algorithm for fabric defect detection on the GPU platform. Compared with the simulation of FFT algorithm based on CPU, the result shows, the algorithm proposed in this...
Information diffusion by social network occurs when a large number of users are involved in the process. Fluid dynamic model has been proved to be an effective method to visualize such information. Fluid dynamic model is extremely time-consuming for large scale computing. Graphics Processing Units (GPU), originally designed for graphics, texture and pixels rendering, now provide computational power...
In a CPU-GPU based heterogeneous computing system, the input data to be processed by the kernel resides in the host memory. The host and the device memory address spaces are different. Therefore, the device can not directly access the host memory. In CUDA programming model, the data is moved between the host memory and the device memory. This data transfer is a time consuming task. The communication...
We present an approach for the maximization of the MIMO channel capacity. The proposed scheme is based on the optimization of the singular values of the channel scattering matrix by properly facing the main computational key points of the problem. The approach is GPU-based, the propagation environment is described by an ultrafast Geometrical Optics (GO) approach, the singular values are computed by...
General purpose computing using GPUs is becoming increasingly popular, because of GPU's extremely favorable performance/price ratio. Like standard processors, GPUs also have a memory hierarchy, which must be carefully optimized for in order to achieve efficient execution. Specifically, modern NVIDIA GPUs have a very small programmable cache, referred to as shared memory, accesses to which are nearly...
Image processing could be done in CPU or in Graphical Processing Unit (GPU), using sequential programming or parallel programming respectively. Sequential and parallel programming are good in their own paradigm. This paper analyses the performances of various basic image processing algorithms on GPU as well as CPU. Various images with a range of dimensions have been used for the testing purpose. The...
Efficient solutions must be considered, in order to solve the problem of intensive computing of the image processing applications and to achieve high real-time performance. The graphics processing unit (GPU) is an effective and the most recent method used for accelerating extensive calculation algorithms to reduce the execution time by exploiting the power of parallel programming techniques and to...
In order to reduce the computing time for processing large tree-structured data sets, parallel processing has been used. Recently, research has been done on parallel computing of tree-structured data on Graphics Processing Units (GPUs). GPU device cannot directly access the tree structured data on hard disks which is commonly stored as objects or linked-lists. So, it is required to copying this tree...
In various applications where the problem domain can be modeled into graphs, the shortest path computation in the graph is an indispensable challenge. In applications like online social networks and shortest route computation problems, the size of the graph is so large; the number of nodes have become close to hundreds of billions. Shortest path graph algorithms like SSSP (Single Source Shortest Path)...
Presently GPU computing is in big call with the sphere of sorting. This paper presents the design of GPU (Graphic Processing Unit) bubble sort with CUDA (Compute Unified Device Architecture) hardware. The bubble sort is considered as comparison based sorting. The design of bubble sort using many core GPUs was previously unknown. The paper also presents the speedup acquired by the GPU bubble. The sorting...
Compute Unified Device Architecture (CUDA) is an attractive alternative for our ever growing need for high performance computing. However to extract the full potential of CUDA one should, at the least be familiar with the programming model and should have a fair understanding of the memory and the cache architecture. Yet most of the domain experts from domains that warrant high performance computing...
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