Abstract. Nonblocking operations have successfully been used to hide network latencies in large scale parallel applications. This paper presents the challenges associated with developing nonblocking collective I/O operations, in order to help hiding the costs of I/O operations. We also present an implementation based on the libNBC library, and evaluate the benefits of nonblocking collective I/O over a PVFS2 file system for a micro-benchmark and a parallel image processing application. Our results indicate the potential benefit of our approach, but also highlight the challenges to achieve appropriate overlap between I/O and compute operations.
In this paper we present a novel cluster paradigm and silicon operating system. Our approach in developing the competent cluster design revolves around an execution model to aid the execution of multiple independent applications simultaneously on the cluster, leading to cost sharing across applications. The execution model should envisage simultaneous execution of multiple applications (running traces of multiple independent applications in the same node at an instant, without time sharing) and on all the partitions(nodes) of a single cluster, without sacrificing the performance of individual application, unlike in the current cluster models. Performance scalability is achieved as we increase the number of nodes, the problem size of the individual independent applications, due to non-dependency across applications and hence increase in the number of non-dependent operations( as the problem sizes of the applications get increased) and this leads to better utilization of the unused resources within the node. This execution model is very much dependent on the node architecture for performance scalability. This would be a major initiative towards achieving performance Cost-Effective Supercomputing.
Agile Software development is now a global phenomenon and is rapidly becoming organizations' most preferred IT process. Extreme Programming (XP) is one of the Agile Methods and Collaborative Pair Programming (CPP) is one of the very important practices of eXtreme Programming. Agile focuses team work which is very important in the field of software development. The software industry has practiced CPP, where two programmers working side by side on one computer on the same problem with great success. Similar experiments have been conducted in academia and pair programming has been shown to be beneficial for both students and teaching staff in university courses. In this study, we conducted some set of experiments about the "human" aspect of the CPP; in particular the effects that personality attributes may have on pair programmer's effectiveness as a pedagogical tool. A formal experiment has been conducted during 2012-13 odd semester at the PSG College of Technology, India to investigate the influence of personality differences among paired students using the five-factor model as a personality measurement framework. The aim of this research is to improve the implementation of CPP as a pedagogical tool to the academic setup through understanding the impact of the variation in the personality profile of paired students towards their academic performance.
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