60294203
A Parallel Loop Self-Scheduling on Extremely Heterogeneous PC Clusters
Cluster computers are a viable and less expensive alternative to symmetric multiprocessor systems. However, a serious difficulty in concurrent programming of a cluster computer system is how to deal with scheduling and load balancing of such a system which may consist of heterogeneous computers Self-scheduling schemes suitable for parallel loops with independent iterations on heterogeneous computer clusters have been designed in the past These schemes, such as FSS, GSS and TSS, can achieve load balancing in SMP, even in a moderate heterogeneous environment, but are not suitable in extremely heterogeneous environments. In this paper, we propose a heuristic approach to solve parallel loop scheduling problems on an extremely heterogeneous PC cluster environment.
12951016
A shareable e-learning platform using data grid technology
Over the past decade, speed in the transmission of knowledge is no longer the way it used to be. Due to this influence, conventional educational methodology has also followed this trend and has gone through a momentous transformation. An excellent example is e-learning which has achieved and broken through the restrictions of time and space. In recent years it has become one of the most popular teaching methods. SCORM (Sharable Course Object Reference Model) the most popular e-learning standard has been adapted from many differing e-learning platforms. Normally, courseware meeting SCORM standards is sharable with other e-learning platforms. Most e-learning platforms however are unable to share courseware directly on the Internet. With this in mind, we have employed one type of grid computing technology called "data grid" in order to achieve this. This technology allows the integration of different SCORM platforms into a huge e-learning environment.
32464432
An Enhanced Parallel Loop Self-Scheduling Scheme for Cluster Environments
In this paper, a parallel loop self-scheduling scheme for heterogeneous PC cluster systems is proposed. Though the proposed scheme does allow users to choose parameters before the execution initialization phase, there are still weaknesses that motivate us to go further with new improvements in that scheme. For instance, a decision on a fixed and monotonous parameter can easily lead to invalid schedule by using previous input information. Thus, it is proposed in this paper a new scheme, where the scheduling parameter can be adjusted dynamically and fit into most widely available computer systems, in order to provide higher overall performance.
7849532
A Peer-to-Peer Resource Sharing System with Data Grid Technology for Mobile Devices
Increases in mobile device processing power, storage capacity, and connectivity in recent years have led to a rapid rise in mobile device use. But mobile users face challenges in making connections with other users in order to share resources. To address this issue, we propose an architecture that uses peer-to-peer protocol to establish a resource sharing platform for mobile devices, combined with a data grid to help analyze and classify resources.
7749374
A Performance-Based Approach to Dynamic Workload Distribution for Master-Slave Applications on Grid Environments
Effective workload distribution techniques can significantly reduce the total completion time of a program on grid computing environments. In this paper, we propose a dynamic performance-based workload partition approach for master-slave types of applications on grids. Furthermore, we implement two types of applications and conduct the experimentations on our grid testbed. Experimental results showed that our method could execute more efficiently than traditional schemes.
5672930
An e-Learning Platform Based on Grid Architecture
The overall popularity of the Internet has helped e-learning become a hot method for learning in recent years. Over the Internet, learners can freely absorb new knowledge without restrictions on time or place. Many companies have adopted e-learning to train their employees. An e-learning system can make an enterprise more competitive by increasing the knowledge of its employees. E-learning has been shown to have impressive potential in e-commerce. At present, most e-learning environment architectures use single computers or servers as their structural foundations. As soon as their work loads increase, their software and hardware must be updated or renewed. This is a big burden on organizations that lack sufficient funds. Thus, in this study we employ a kind of Grid Computing technology, called the ”Data Grid” to integrate idle computer resources in enterprises into e-learning platforms, thus eliminating the need to purchase costly high-level servers and other equipment.
5809817
Efficient Kernel Machines Using the Improved Fast Gauss Transform
The computation and memory required for kernel machines with N training samples is at least O(N2). Such a complexity is significant even for moderate size problems and is prohibitive for large datasets. We present an approximation technique based on the improved fast Gauss transform to reduce the computation to O(N). We also give an error bound for the approximation, and provide experimental results on the UCI datasets.
14016299
Building Parallel Corpora by Automatic Title Alignment
Cross-lingual semantic interoperability has drawn significant research attention recently, as the number of digital libraries in non-English languages has grown exponentially. Cross-lingual information retrieval (CLIR) across different European languages, such as English, Spanish and French, has been widely explored, but CLIR across European and Oriental languages is still at the initial stages. To cross the language boundary, a corpus-based approach shows promise of overcoming the limitations of knowledge-based and controlled vocabulary approaches. However, collecting parallel corpora between European and Oriental languages is not an easy task. Length-based and text-based approaches are two major approaches to align parallel documents. In this paper, we investigate several techniques using these approaches, and compare their performance in aligning English and Chinese titles of parallel documents available on the Web.
9021705
Integrated volume compression and visualization
Volumetric data sets require enormous storage capacity even at moderate resolution levels. The excessive storage demands not only stress the capacity of the underlying storage and communications systems, but also seriously limit the speed of volume rendering due to data movement and manipulation. A novel volumetric data visualization scheme is proposed and implemented in this work that renders 2D images directly from compressed 3D data sets. The novelty of this algorithm is that rendering is performed on the compressed representation of the volumetric data without pre-decompression. As a result, the overheads associated with both data movement and rendering processing are significantly reduced. The proposed algorithm generalizes previously proposed whole-volume frequency-domain rendering schemes by first dividing the 3D data set into subcubes, transforming each subcube to a frequency-domain representation, and applying the Fourier projection theorem to produce the projected 2D images according to given viewing angles. Compared to the whole-volume approach, the subcube-based scheme not only achieves higher compression efficiency by exploiting local coherency, but also improves the quality of resultant rendering images because it approximates the occlusion effect on a subcube by subcube basis.
6650274
Building parallel corpora by automatic title alignment using length-based and text-based approaches
Cross-lingual semantic interoperability has drawn significant attention in recent digital library and World Wide Web research as the information in languages other than English has grown exponentially. Cross-lingual information retrieval (CLIR) across different European languages, such as English, Spanish, and French, has been widely explored; however, CLIR across European languages and Oriental languages is still in the initial stage. To cross language boundary, corpus-based approach is promising to overcome the limitation of the knowledge-based and controlled vocabulary approaches but collecting parallel corpora between European language and Oriental language is not an easy task. Length-based and text-based approaches are two major approaches to align parallel documents. In this paper, we investigate several techniques using these approaches and compare their performances in aligning English and Chinese titles of parallel documents available on the Web.
10638554
Near-optimal regularization parameters for applications in computer vision
Computer vision requires the solution of many ill-posed problems such as optical flow, structure from motion, shape from shading, surface reconstruction, image restoration and edge detection. Regularization is a popular method to solve ill-posed problems, in which the solution is sought by minimization of a sum of two weighted terms, one measuring the error arising from the ill-posed model, the other indicating the distance between the solution and some class of solutions chosen on the basis of prior knowledge (smoothness, or other prior information). One of important issues in regularization is choosing optimal weight (or regularization parameter). Existing methods for choosing regularization parameters either require the prior information on noise in the data, or are heuristic graphical methods. We apply a method for choosing near-optimal regularization parameters by approximately minimizing the distance between the true solution and the family of regularized solutions. We demonstrate the effectiveness of this approach for the regularization on two examples: edge detection and image restoration.