1,720,973 research outputs found
Analyzing fault behavior of shared data in parallel applications
No full textMulticore architectures are becoming the most promising computing platforms thanks to their high performance. The soft error rate in multicore systems increases by the trend in the transistor sizes and the reduction of the voltage of the transistors. Evaluating the impact of soft errors on parallel applications is critical to understand the fault characteristics and to decide the fault tolerance strategies for the reliable execution. In this paper, we examine the soft error vulnerabilities of shared data in parallel Java applications. To analyze fault behavior of shared data in parallel programs, we design and implement a bytecode instrumentation based analysis and fault injection framework. We evaluate the fault behavior of shared data fields on a set of parallel applications from NAS benchmark suite. Our experimental evaluation demonstrates data type and access characteristics of the shared fields, and shows that shared data structures of parallel applications are more vulnerable to soft errors. While error rates for unshared local data stay around 20% in our target applications, the rate for shared data exceeds above 30% for some applications. We further discuss potential directions of our results and how shared data analysis can be employed to apply partial fault tolerance techniques. (C) 2016 Elsevier B.V. All rights reserved
Predicting the Soft Error Vulnerability of Parallel Applications Using Machine Learning
No full textWith the widespread use of the multicore systems having smaller transistor sizes, soft errors become an important issue for parallel program execution. Fault injection is a prevalent method to quantify the soft error rates of the applications. However, it is very time consuming to perform detailed fault injection experiments. Therefore, prediction-based techniques have been proposed to evaluate the soft error vulnerability in a faster way. In this work, we present a soft error vulnerability prediction approach for parallel applications using machine learning algorithms. We define a set of features including thread communication, data sharing, parallel programming, and performance characteristics; and train our models based on three ML algorithms. This study uses the parallel programming features, as well as the combination of all features for the first time in vulnerability prediction of parallel programs. We propose two models for the soft error vulnerability prediction: (1) A regression model with rigorous feature selection analysis that estimates correct execution rates, (2) A novel classification model that predicts the vulnerability level of the target programs. We get maximum prediction accuracy rate of 73.2% for the regression-based model, and achieve 89% F-score for our classification model
A Survey on Multithreading Alternatives for Soft Error Fault Tolerance
No full textSmaller transistor sizes and reduction in voltage levels in modern microprocessors induce higher soft error rates. This trend makes reliability a primary design constraint for computer systems. Redundant multithreading (RMT) makes use of parallelism in modern systems by employing thread-level time redundancy for fault detection and recovery. RMT can detect faults by running identical copies of the program as separate threads in parallel execution units with identical inputs and comparing their outputs. In this article, we present a survey of RMT implementations at different architectural levels with several design considerations. We explain the implementations in seminal papers and their extensions and discuss the design choices employed by the techniques. We review both hardware and software approaches by presenting the main characteristics and analyze the studies with different design choices regarding their strengths and weaknesses. We also present a classification to help potential users find a suitable method for their requirement and to guide researchers planning to work on this area by providing insights into the future trend
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
A meta-heuristic based three-dimensional path planning environment for unmanned aerial vehicles
No full textUnmanned Aerial Vehicles (UAVs) are used for many missions, including weather reconnaissance, search and rescue assisting operations over seas and mountains, aerial photographing and mapping, fire detection, and traffic control. Autonomous operation of UAVs requires the development of control systems that can work without human support for long time periods. The path planners, which generate collision-free and optimized paths, are needed to provide autonomous operation capabilities to the UAVs. The optimization of the flight trajectory is a multi-objective problem dealing with variable terrain features as well as dynamic environment conditions. This paper presents a simulation environment for offline path planning of unmanned aerial vehicles on three-dimensional terrains. Our path planner aims to identify the shortest path and/or flight envelope in a given line of sight by avoiding terrain collisions, traveling on a path that stays within the restricted minimum and maximum distances above the terrain, traveling far from the specified threat zones, and maneuvering with an angle greater than the minimum curvature radius. We present two meta-heuristics (genetic algorithms and hyper-heuristics) in order to construct the paths for UAV navigation and compare our results with a reference work given in the literature. A comparative study over a set of terrains with various characteristics validates the effectiveness of the proposed meta-heuristics, where the quality of a solution is measured with the total cost of a constructed path, including the penalties of all constraints
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
A user-assisted thread-level vulnerability assessment tool
No full textThe system reliability becomes a critical concern in modern architectures with the scale down of circuits. To deal with soft errors, the replication of system resources has been used at both hardware and software levels. Since the redundancy causes performance degradation, it is required to explore partial redundancy techniques that replicate the most vulnerable parts of the code. The redundancy level of user applications depends on user preferences and may be different for the users with different requirements. In this work, we propose a user-assisted reliability assessment tool based on critical thread analysis for redundancy in parallel architectures. Our analysis evaluates the application threads of a parallel program by considering their criticality in the execution and selects the most critical thread or threads to be replicated. Moreover, we extend our analysis by exploring critical regions of individual threads and execute redundantly only those regions to reduce redundancy overhead. Our experimental evaluation indicates that the replication of the most critical thread improves the system reliability more (up to 10% for blackscholes application) than the replication of any other thread. The partial thread replication based on critical region analysis also reduces the vulnerability of the system by considering a fine-grained approach
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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