Abstract

We describe the Nimrod/O distributed optimization tool and its application to a problem in mechanical design. The problem is to determine the shape for a hole in a thin plate under load that gives optimal life in the presence of flaws. The experiment reveals two distinct design strategies for optimizing this life. Nimrod/O is able to find both of these rapidly due to its inherent parallelism.

Bumigora University College there are several things that are not balanced between the entry and exit of students who have completed their studies. Students who enter in large numbers, but students who graduate on time below the specified standards. As result, there was a huge accumulation of students in each graduation period. One solution to overcome the problem above needs a data mining based system in monitoring or utilizing student development in predicting graduation using the C4.5 algorithm. The stages of this research began with problem analysis, data collection, data requirement analysis, data design, coding, and testing. The results of this study are the implementation of the C4.5 algorithm for predicting student graduation on time or not. The data used is the data of students who have graduated from 2010 to 2012. The level of acceptance generated using the confusion matrix is ​​93,103% accuracy using 163 training data and 29 testing data or 85% training data and 15% testing data. The results of research and testing that has been done, C4.5 algorithm is very suitable to be used in student graduation prediction.

Relative Debugging allows a user to compare the internal state of two programs as they run, making it possible to test whether two programs perform the same function given the same input. When implemented with a command line user interface, a relative debugger looks like traditional debugging tools with the addition of commands that describe which structures should be equivalent in the two programs. In this paper, we discuss relative debugging within an integrated development environment, and show that there are significant advantages over a command line form. We describe a pluggable, modular, architecture that works with a variety of different products, including Microsoft's Visual Studio, SUN's NetBeans, and IBM's Eclipse. Copyright © 2009 John Wiley & Sons, Ltd.

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Abstract-Programminglanguages have advanced tremendously over the years, but program debuggers have hardly changed. Sequential debuggers do little more than allow a user to control the flow of a program and examine its state. Parallel ones support the same operations on multiple processes, which are adequate with a small number of processors, but become unwieldy and ineffective on very large machines. Typical scientific codes have enormous multidimensional data structures and it is impractical to expect a user to view the data using traditional display techniques. In this paper we discuss the use of debug-time assertions, and show that these can be used to debug parallel programs. The techniques reduce the debugging complexity because they reason about the state of large arrays without requiring the user to know the expected value of every element. Assertions can be expensive to evaluate, but their performance can be improved by running them in parallel. We demonstrate the system with a case study finding errors in a parallel version of the Shallow Water Equations, and evaluate the performance of the tool on a 4,096 cores Cray XE6.

Grid computing facilitates the aggregation and coordination of resources that are distributed across multiple administrative domains for large-scale and complex e-Science experiments. Writing, deploying, and testing grid applications over highly heterogeneous and distributed resources are complex and challenging. The process requires grid-enabled programming tools that can handle the complexity and scale of the infrastructure. However, while a large amount of research has been undertaken into grid middleware, little work has been directed specifically at the area of grid application development tools. This paper presents the design and implementation of ISENGARD, an infrastructure for supporting e-Science and grid application development. ISENGARD provides services, tools, and APIs that simplify grid software development.