3,236 research outputs found

    An EPIIC Vision to Evolve Project Integration, Innovation, and Collaboration with Broad Impact for How NASA Executes Complex Projects

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    Evolving Project Integration, Innovation, and Collaboration (EPIIC) is a vision defined to transform the way projects manage information to support real-time decisions, capture best practices and lessons learned, perform assessments, and manage risk across a portfolio of projects. The foundational project management needs for data and information will be revolutionized through innovations on how we manage and access that data, implement configuration control, and certify compliance. The embedded intelligence of new interactive data interfaces integrate technical and programmatic data such that near real time analytics can be accomplished to more efficiently and accurately complete systems engineering and project management tasks. The system-wide data analytics that are integrated into customized data interfaces allows the growing team of engineers and managers required to develop and implement major NASA missions the ability to access authoritative source(s) of system information while greatly reducing the labor required to complete system assessments. This would allow, for example, much of what is accomplished in a scheduled design review to take place as needed, between any team members, at any time. An intelligent data interface that rigorously integrates systems engineering and project management information in near real time can provide substantially greater insight for systems engineers, project managers, and the large diverse teams required to complete a complex project. System engineers, programmatic personnel (those who focus on cost, schedule, and risk), the technical engineering disciplines, and project management can realize immediate benefit from the shared vision described herein. Implementation of the vision also enables significant improvements in the performance of the engineered system being developed

    Towards Loosely-Coupled Programming on Petascale Systems

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    We have extended the Falkon lightweight task execution framework to make loosely coupled programming on petascale systems a practical and useful programming model. This work studies and measures the performance factors involved in applying this approach to enable the use of petascale systems by a broader user community, and with greater ease. Our work enables the execution of highly parallel computations composed of loosely coupled serial jobs with no modifications to the respective applications. This approach allows a new-and potentially far larger-class of applications to leverage petascale systems, such as the IBM Blue Gene/P supercomputer. We present the challenges of I/O performance encountered in making this model practical, and show results using both microbenchmarks and real applications from two domains: economic energy modeling and molecular dynamics. Our benchmarks show that we can scale up to 160K processor-cores with high efficiency, and can achieve sustained execution rates of thousands of tasks per second.Comment: IEEE/ACM International Conference for High Performance Computing, Networking, Storage and Analysis (SuperComputing/SC) 200

    Exploring the Public Perception in Social Big Data: An Investigation in Mars Recall Scandal

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    Social media has become a popular platform of interpersonal communication in which users can search for news and convey real-time information. Researching into social big data, such as Twitter, can be an effective way to identify public opinions and feelings in risk emergence, as it provides rich sources of data for opinion mining and sentiment analysis. This study aims to investigate and analyse the public perception towards the Mars and Snickers product recall scandal. The study proposes a comprehensive data analysis framework, and utilises the dataset formed of 10,930 Twitter messages over the span of 10-day following the product recall announcement made by Mars Inc., to gauge public attitudes and opinions. The study finds that the overall attitude of Twitter users towards the scandal was negative, and Snickers were the most mentioned product in the 10-day periods after the announcement of the recall. The data analysis highlights that the Tweet diffusion (retweeting) has positive associations with the number of followers and the use of hashtags, hence companies should pay more attention to users who have a large number of followers, as their tweets will be read by a great number of other Twitter users. The findings suggest effective methods for practitioners in crisis management (e.g., how to use social media to disseminate information). The study also presents a progressive tweet-mining framework that can serve as a tool in crisis management to classify the tweet topics, identify and analyse the sentiment and comprehend the changes of the public attitudes

    Nebulae: A Proposed Concept of Operation for Deep Space Computing Clouds

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    In this paper, we describe an ongoing multi-institution study in using emplaced computational resources such as high-volume storage and fast processing to enable instruments to gather and store much more data than would normally be possible, even if it cannot be downlinked to Earth in any reasonable time. The primary focus of the study is designing science pipelines for on-site summarization, archival for future downlink, and multisensor fusion. A secondary focus is on providing support for increasingly autonomous systems, including mapping, planning, and multi-platform collaboration. Key to both of these concepts is treating the spacecraft not as an autonomous agent but as an interactive batch processor, which allows us to avoid “quantum leaps” in machine intelligence required to realize the concepts. Our goal is to discuss preliminary results and technical directions for the community, and identify promising new opportunities for multi-sensor fusion with the help of planetary researchers
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