Parallel programming is about performance, for otherwise we’d write a sequential program. A problem is where to find truly parallel hardware that can be dedicated to the task, One answer is graphical processing units (GPUs), which can have hundreds of cores and are found in millions of desktop and laptop computers. GPU computing with Open CL is a new approach to computing where hundreds of on-c...

Self-Organizing Maps (SOM) is a widely used artificial neural network (ANN) model. Because of its heavy computation load when the map is big and inherent parallel, there is a need to apply a parallel algorithm on it. As a SIMD parallel processor, Graphic processing unit (GPU) shows a fast growing speed than CPU. And it also provides programmability recently. In this paper, the algorithm and res...

This paper discusses issues related to GPU for Economic problems. It highlights new methodologies and resources that are available for solving and estimating economic models and emphasizes situations when they are useful and others where they are impractical. Two examples illustrate the different ways these GPU parallel methods can be employed to speed computation.

Multi-core based high performance computing systems are available with a reasonable price. Parallel programming paradigm needs to be adjusted to an individual system. Parallel computing systems were compared in this paper. Electroencephalography signals were collected in order to measure performance of parallel computing for CPU and GPU based systems. A CPU based system showed better performanc...

Various types of two-body statistics (2-BS) are regarded as essential components of data analysis in many scientific and computing domains. Due to the quadratic time complexity, use of modern parallel hardware has become an obvious direction for research and practice in 2-BS computation. This paper presents our recent work in designing and optimizing parallel algorithms for 2-BS computation on ...

noise removal operation is commonly applied as pre-processing step before subsequent image processing tasks due to the occurrence of noise during acquisition or transmission process. a common problem in imaging systems by using cmos or ccd sensors is appearance of  the salt and pepper noise. this paper presents cellular automata (ca) framework for noise removal of distorted image by the salt an...

As a powerful and flexible processor, the Graphic Processing Unit (GPU) can offer a great faculty in solving many high-performance computing applications. Sweep3D, which simulates a single group time-independent discrete ordinates (Sn) neutron transport deterministically on 3D Cartesian geometry space, represents the key part of a real ASCI application. The wavefront process for parallel comput...

This paper surveys the contents of the special issue on Emerging Computational Methods for the Life Sciences Workshop 2012 with six contributed papers. They cover a rich variety of topics on interface of life sciences and data intensive computation which in detail are parallelization with GPU and multicore of an important tandem mass spectrometry peptide identification tool MyriMatch; enhanceme...

The network anomaly detection technology based on support vector machine (SVM) can efficiently detect unknown attacks or variants of known attacks, however, it cannot be used for detection of large-scale intrusion scenarios due to the demand of computational time. The graphics processing unit (GPU) has the characteristics of multi-threads and powerful parallel processing capability. Based on th...

A new method is presented for rendering general FRep (functionally represented) models using GPU-accelerated ray casting. We use the GPU acceleration for all computations in the rendering algorithm: ray-surface intersection calculation, function evaluation, and normal vector computation. Performing geometric intersection calculations in parallel with shading allows us to combine the whole proce...