2733911
A Hybrid Parallel Loop Scheduling Scheme on Heterogeneous PC Clusters
Traditional loop-scheduling schemes are designed for homogeneous computing environments, and are probably not suitable for emerging heterogeneous PC clusters. This paper applies a two-phased method, named HPLS (Hybrid Parallel Loop Scheduling), to heterogeneous PC-cluster environments. The key idea is to distribute most of the workload to each node according to its performance, which is modeled and estimated in advance. Experiments on our testbed PCcluster showed that, in most cases, our method could reduce the execution time of application programs more than previous schemes could.
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.
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.
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.
1555973
All-du-path coverage for parallel programs
One significant challenge in bringing the power of parallel machines to application programmers is providing them with a suite of software tools similar to the tools that sequential programmers currently utilize. In particular, automatic or semi-automatic testing tools for parallel programs are lacking. This paper describes our work in automatic generation of all-du-paths for testing parallel programs. Our goal is to demonstrate that, with some extension, sequential test data adequacy criteria are still applicable to parallel program testing. The concepts and algorithms in this paper have been incorporated as the foundation of our DELaware PArallel Software Testing Aid, della pasta.
14482578
Segmenting Chinese Unknown Words by Heuristic Method
Chinese text segmentation is important in Chinese text indexing. Due to the lack of word delimiters in Chinese text, Chinese text segmentation is more difficult than English text segmentation. Besides, the segmentation ambiguities and the occurrences of out-of-vocabulary words (i.e. unknown words) are the major challenges in Chinese segmentation. Many research works dealing with the problem of word segmentation have focused on the resolution of segmentation ambiguities. The problem of unknown word identification has not drawn much attention. In this paper, we propose a heuristic method for Chinese test segmentation based on the statistical approach. The experimental result shows that our proposed heuristic method is promising to segment the unknown words as well as the known words. We have further investigated the distribution of the errors of commission and the errors of omission caused by the proposed heuristic method and benchmarked the proposed heuristic method with our previous proposed technique, boundary detection.
6473756
A vector space model for automatic indexing
In a document retrieval, or other pattern matching environment where stored entities (documents) are compared with each other or with incoming patterns (search requests), it appears that the best indexing (property) space is one where each entity lies as far away from the others as possible; in these circumstances the value of an indexing system may be expressible as a function of the density of the object space; in particular, retrieval performance may correlate inversely with space density. An approach based on space density computations is used to choose an optimum indexing vocabulary for a collection of documents. Typical evaluation results are shown, demonstating the usefulness of the model.
7536937
An algorithm for all-du-path testing coverage of shared memory parallel programs
Little attention has focused on applying traditional testing methodology to parallel programs. This paper discusses issues involved in providing all-du-path coverage in shared memory parallel programs, and describes an algorithm for finding a set of paths covering all define-use pairs. To our knowledge, this is the first effort of this kind.
5563875
Intelligent agents for retrieving chinese Web financial news
As the popularity of World Wide Web increases, many newspapers expand their services by providing news information on the Web in order to be competitive and increase benefit. The Web provides real time dissemination of financial news to investors. However, most investors find it difficult to search for the financial information of interest from the huge Web information space. Most of the commercial search engines are not user friendly and do not provide any tailor-made intelligent agents to search for relevant Web documents on behalf of users. Users have to exert a lot of effort to submit an appropriate query to obtain the information they want. Intelligent agents that learn user preferences and monitor the postings of Web information providers are desired. In this paper, we present an intelligent agent that utilizes user profiles and user feedback to search for the Chinese Web financial news articles on behalf of users. A Chinese indexing component is developed to index the continuously fetched Chinese financial news articles. User profiles capture the basic knowledge of user preferences based on the sources of news articles, the regions of the news reported, categories of industries related, the listed companies, and user specified keywords. User feedback captures the semantics of the user rated news articles. The search engine will rank the top 20 news articles that users are most interested in based on these inputs. Experiments were conducted to measure the performance of the agents based on the inputs from user profile and user feedback.