Towards Grid Interoperability

The Grid paradigm promises to provide global access to computing resources, data storage and experimental instruments. It also provides an elegant solution to many resource administration and provisioning problems while offering a platform for collaboration and resource sharing. Although substantial progress has been made towards these goals, nevertheless there is still a lot of work to be done until the Grid can deliver its promises. One of the central issues is the development of standards and Grid interoperability. Job execution is one of the key capabilities in all Grid environments. This is a well understood, mature area with standards and implementations. This paper describes some proof of concept experiments demonstrating the interoperability between various Grid environments

Exploiting operating system services to efficiently checkpoint parallel applications in GENESIS

Recent research efforts of parallel processing on non-dedicated clusters have focused on high execution performance, parallelism management, transparent access to resources, and making clusters easy to use. However, as a collection of independent computers used by multiple users, clusters are susceptible to failure. This paper shows the development of a coordinated checkpointing facility for the GENESIS cluster operating system. This facility was developed by exploiting existing operating system services. High performance and low overheads are achieved by allowing the processes of a parallel application to continue executing during the creation of checkpoints, while maintaining low demands on cluster resources by using coordinated checkpointing.<br /

Activities at the Lunar and Planetary Institute

The scientific and administrative activities of the Lunar and Planetary Institute are summarized. Recent research relating to geophysics, planetary geology, the origin of the Earth and Moon, the lunar surface, Mars, meteorites, and image processing techniques is discussed

A Survey on Compiler Autotuning using Machine Learning

Since the mid-1990s, researchers have been trying to use machine-learning based approaches to solve a number of different compiler optimization problems. These techniques primarily enhance the quality of the obtained results and, more importantly, make it feasible to tackle two main compiler optimization problems: optimization selection (choosing which optimizations to apply) and phase-ordering (choosing the order of applying optimizations). The compiler optimization space continues to grow due to the advancement of applications, increasing number of compiler optimizations, and new target architectures. Generic optimization passes in compilers cannot fully leverage newly introduced optimizations and, therefore, cannot keep up with the pace of increasing options. This survey summarizes and classifies the recent advances in using machine learning for the compiler optimization field, particularly on the two major problems of (1) selecting the best optimizations and (2) the phase-ordering of optimizations. The survey highlights the approaches taken so far, the obtained results, the fine-grain classification among different approaches and finally, the influential papers of the field.Comment: version 5.0 (updated on September 2018)- Preprint Version For our Accepted Journal @ ACM CSUR 2018 (42 pages) - This survey will be updated quarterly here (Send me your new published papers to be added in the subsequent version) History: Received November 2016; Revised August 2017; Revised February 2018; Accepted March 2018

Effective Scheduling of Grid Resources Using Failure Prediction

In large-scale grid environments, accurate failure prediction is critical to achieve effective resource allocation while assuring specified QoS levels, such as reliability. Traditional methods, such as statistical estimation techniques, can be considered to predict the reliability of resources. However, naive statistical methods often ignore critical characteristic behavior of the resources. In particular, periodic behaviors of grid resources are not captured well by statistical methods. In this paper, we present an alternative mechanism for failure prediction. In our approach, the periodic pattern of resource failures are determined and actively exploited for resource allocation with better QoS guarantees. The proposed scheme is evaluated under a realistic simulation environment of computational grids. The availability of computing resources are simulated according to real trace that was collected from our large-scale monitoring experiment on campus computers. Our evaluation results show that the proposed approach enables significantly higher resource scheduling effectiveness under a variety of workloads compared to baseline approaches

Can This Marriage Be Saved?

Market forces in health care are paradoxically pulling physicians and hospitals apart and together at the same time. What are these forces and trends? Is the long-standing marriage of interdependence and productivity between them destined to fail, or can it be saved and even strengthened by emerging delivery and governance models in the so-called "market revolution" of consumer-driven health care? What are the implications for health care policy and practice? These are issues we explore in this Arizona Health Futures Policy Primer

Peace education, militarism and neo-liberalism: conceptual reflections with empirical findings from the UK

This article explores ‘peace days’ in English schools as a form of peace education. From a historical overview of academic discussions on peace education in the US and Great Britain since the First World War, we identify three key factors important for peace education: the political context, the place in which peace days occur and pedagogical imperatives of providing a certain narrative of the sources of violence in politics. Although contemporary militarism and neoliberalism reduce the terrains for peace studies in English schools, peace days allow teachers to carve out spaces for peace education. Peace days in Benfield School, Newcastle and Comberton Village College, Cambridgeshire, are considered as case studies. We conclude with reflections on the opportunities and limitations of this approach to peace education, and on how peace educators and activists could enlarge its reach

Avida: a software platform for research in computational evolutionary biology

Avida is a software platform for experiments with self-replicating and evolving computer programs. It provides detailed control over experimental settings and protocols, a large array of measurement tools, and sophisticated methods to analyze and post-process experimental data. We explain the general principles on which Avida is built, as well as its main components and their interactions. We also explain how experiments are set up, carried out, and analyzed