Fault-Tolerant Dynamic Rescheduling for Heterogeneous Computing Systems

As the scale and complexity of heterogeneous computing systems grow, failures occur frequently and have an adverse effect on solving large-scale applications. Hence, fault-tolerant scheduling is an imperative step for large-scale computing systems. The existing fault-tolerant scheduling algorithms belong to static scheduling, and they allocate multiple copies of each task to several processors no matter whether processor failures affect the execution of tasks. Such active replication strategies not only waste resource but also sacrifice the makespan. What is more, they cannot guarantee the successful execution of applications. In this paper, we propose a fault-tolerant dynamic rescheduling algorithm named FTDR, which can overcome above drawbacks. FTDR keeps listening to the processor failure, and reschedules the suspended tasks once failures occur. Because FTDR reschedules the tasks that are suspended because of failures, it can tolerate an arbitrary number of failures. Randomly generated DAGs are tested in our experiments. Experimental results show that the proposed algorithm achieves good performance in terms of makespan and resource consumption compared with its direct competitors.     

Improving MapReduce Performance with Partial Speculative Execution

The MapReduce framework has become the de facto standard for big data processing due to its attractive features and abilities. One is that it automatically parallelizes a job into multiple tasks and transparently handles task execution on a large cluster of commodity machines. The increasing heterogeneity of distributed environments may result in a few straggling tasks, which prolong job completion. Speculative execution is proposed to mitigate stragglers. However, the existing speculative execution mechanism could not work efficiently as many speculative tasks are still slower than their original tasks. In this paper, we explore an approach to increase the efficiency of speculative execution, and further improve MapReduce performance. We propose the Partial Speculative Execution (PSE) strategy to make speculative tasks start from the checkpoint. By leveraging the checkpoint of original tasks, PSE can eliminate the costs of re-reading, re-copying, and re-computing the processed data. We implement PSE in Hadoop, and evaluate its performance in terms of job completion time and the efficiency of speculative execution under several kinds of classical workloads. Experimental results show that, in heterogeneous environments with stragglers, PSE completes jobs 56 % faster than that with no speculation and 12 % faster than that with LATE, an improved speculative execution algorithm. In addition, on average PSE can improve the efficiency of speculative execution by 24 % compared to LATE.     

Leon Battista Alberti as Author of <Emphasis Type="Italic">Hypnerotomachia Poliphili</Emphasis>

The enigmatic Hypnerotomachia Poliphili published anonymously in 1499 has long posed puzzles for historians and other scholars. This present text argues that the volume can credibly be attributed, not to Francesca Colonna as is often done, but to the Renaissance humanist and polymath Leon Battista Alberti. Evidence for this is found in the unravelling of arithmogrammatical evidence sprinkled throughout the work, similar to those found in other of Alberti’s works.     

Shifted robust multi-objective test problems

In 2013 Gaspar-Cunha et al. proposed a set of novel robust multi-objective benchmark functions to increase the difficulty of the current test problems and effectively mimic the characteristics of real search spaces. Despite the merits of the proposed benchmark problems, it is observed that the robust Pareto optimal fronts are located on the boundaries of the search space, which may result in the infeasibility of solutions obtained in case of perturbations along the negative side of the second parameter. This paper modifies the proposed test functions by Gaspar-Cunha et al. to mimic real problems better and allow the parameters to be fluctuated by any degree of perturbations. In fact, the robust fronts are shifted to the centre of the search space, so that any degree of uncertainties can be considered. The paper considers theoretical and experimental analysis of both set of test functions as well.     

Creating geometrically robust designs for highly sensitive problems using topology optimization

Resonance and wave-propagation problems are known to be highly sensitive towards parameter variations. This paper discusses topology optimization formulations for creating designs that perform robustly under spatial variations for acoustic cavity problems. For several structural problems, robust topology optimization methods have already proven their worth. However, it is shown that direct application of such methods is not suitable for the acoustic problem under consideration. A new double filter approach is suggested which makes robust optimization for spatial variations possible. Its effect and limitations are discussed. In addition, a known explicit penalization approach is considered for comparison. For near-uniform spatial variations it is shown that highly robust designs can be obtained using the double filter approach. It is finally demonstrated that taking non-uniform variations into account further improves the robustness of the designs.     

3D interactive topology optimization on hand-held devices

This educational paper describes the implementation aspects, user interface design considerations and workflow potential of the recently published TopOpt 3D App. The app solves the standard minimum compliance problem in 3D and allows the user to change design settings interactively at any point in time during the optimization. Apart from its educational nature, the app may point towards future ways of performing industrial design. Instead of the usual geometrize, then model and optimize approach, the geometry now automatically adapts to the varying boundary and loading conditions. The app is freely available for iOS at Apple’s App Store and at http://www.topopt.dtu.dk/TopOpt3D for Windows and OSX.     

Experiment and multiobjective optimization design of tape-spring hinges

Flexible tape-spring hinges can be folded elastically and are able to self-deploy by releasing stored strain energy with fewer component parts and slight weights. This study presents a detailed investigation of the folding and deployment of single-layer tape-spring (SLTS) hinges and double-layer tape-spring (DLTS) hinges under pure bend loading. The material properties of tape-spring hinges are measured using an INSTRON machine. A DLTS hinge construction is created, and its moment-rotation relationship during quasi-static deployment is measured. An experiment is conducted to verify the validation of the numerical models for the DLTS hinges. The quasi-static deployment behavior of SLTS hinges and DLTS hinges is then analyzed using nonlinear finite element ABAQUS/Explicit solver, starting from the complete folded configuration. The DLTS hinge has good quasi-static deployment performances with regard to maximum stress (S _m ), steady moment (M ^*) and the peak moment (M _d ) during the DLTS hinge quasi-static deployment. In addition, the sampling designs of the DLTS hinges are created based on a three-level full factorial design of experiments (DOE) method. The surrogate models of S _m , M ^* and M _d of the DLTS hinges are derived using response surface method (RSM) to reduce the computational cost of quasi-static folding and deployment of numerical simulations. The Multiobjective optimization design (MOD) of the DLTS hinge is performed using modified non-dominated sorting genetic algorithm (NSGA-II) algorithm to achieve the optimal design. The finite element models for the optimal design based on numerical method are established to validate the optimization results.     

Comparative evaluation of performance measures for human driving skills

In this paper, we evaluate the adequacy of several performance measures for the evaluation of driving skills between different drivers. This work was motivated by the need for a training system that captures the driving skills of an expert driver and transfers the skills to novice drivers using a haptic-enabled driving simulator. The performance measures examined include traditional task performance measures, e.g., the mean position error, and a stochastic distance between a pair of hidden Markov models (HMMs), each of which is trained for an individual driver. The emphasis of the latter is on the differences between the stochastic somatosensory processes of human driving skills. For the evaluation, we developed a driving simulator and carried out an experiment that collected the driving data of an expert driver whose data were used as a reference for comparison and of many other subjects. The performance measures were computed from the experimental data, and they were compared to each other. We also collected the subjective judgement scores of the driver’s skills made by a highly-experienced external evaluator, and these subjective scores were compared with the objective performance measures. Analysis results showed that the HMM-based distance metric had a moderately high correlation between the subjective scores and it was also consistent with the other task performance measures, indicating the adequacy of the HMM-based metric as an objective performance measure for driving skill learning. The findings of this work can contribute to developing a driving simulator for training with an objective assessment function of driving skills.     

More of the Same? Understanding Transformation in Tablet-based Academic Library Instruction

Academic librarians have shared their experiences with tablet computers, but few examine how librarians use tablets in their instruction design. While the education literature provides technology integration models, the nature of library instruction requires adapting these models to the library classroom. After reviewing literature related to tablets in library instruction and a number of technology integration frameworks, this article demonstrates an application of the Substitution, Augmentation, Modification, Redefinition framework to analyze observations of an iPad-equipped classroom at a university library. Demonstrating this use of a framework provides an approach to technology integration and continues the discussion about tablets’ potential to promote innovative pedagogy.