2017 IEEE 19th International Conference on High Performance Computing and Communications; IEEE 15th International Conference on Smart City; IEEE 3rd International Conference on Data Science and Systems (HPCC/SmartCity/DSS)

18-20 Dec. 2017

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  • [Title page i]

    Publication Year: 2017, Page(s): i
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  • [Title page iii]

    Publication Year: 2017, Page(s): iii
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  • [Copyright notice]

    Publication Year: 2017, Page(s): iv
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  • Table of contents

    Publication Year: 2017, Page(s):v - xiv
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  • HPCC/SmartCity/DSS 2017 Message from the General Chairs

    Publication Year: 2017, Page(s):xv - xvi
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  • HPCC 2017 Message from the Program Chairs

    Publication Year: 2017, Page(s):xvii - xviii
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  • SmartCity 2017 Message from the Program Chairs

    Publication Year: 2017, Page(s): xix
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  • DSS 2017 Message from the Program Chairs

    Publication Year: 2017, Page(s): xx
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  • HPCC 2017 Organizing Committee

    Publication Year: 2017, Page(s): xxi
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  • SmartCity 2017 Organizing Committee

    Publication Year: 2017, Page(s): xxii
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  • DSS 2017 Organizing Committee

    Publication Year: 2017, Page(s): xxiii
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  • HPCC 2017 Program Committee

    Publication Year: 2017, Page(s):xxiv - xxv
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  • SmartCity 2017 Program Committee

    Publication Year: 2017, Page(s):xxvi - xxvii
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  • DSS 2017 Program Committee

    Publication Year: 2017, Page(s):xxviii - xxix
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  • HPCC 2017 Steering Committee

    Publication Year: 2017, Page(s): xxx
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  • SmartCity 2017 Steering Committee

    Publication Year: 2017, Page(s): xxxi
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  • DSS 2017 Steering Committee

    Publication Year: 2017, Page(s): xxxii
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  • Sponsors

    Publication Year: 2017, Page(s): xxxiii
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  • HPCC/SmartCity/DSS 2017 Proceedings Co-Editors

    Publication Year: 2017, Page(s): xxxiv
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  • Plenary Panel: Convergence of High-Performance Computing and Communication, Smart City, and Data Sciences and Systems: Fields Helping Grand Challenges and Each Other

    Publication Year: 2017, Page(s): xxxv
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  • Analysis and Modeling of the End-to-End I/O Performance on OLCF's Titan Supercomputer

    Publication Year: 2017, Page(s):1 - 9
    Cited by:  Papers (1)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (603 KB) | HTML iconHTML

    With the increase of scale and complexity seen in a variety of leadership-class scientific computation and simulation applications, it has become more important to understand their I/O performance characteristics. The user-observed performance is a combination of properties of how the application is using the HPC facility, as well as how others' use of the facility causes variability in the static... View full abstract»

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  • Portable Parallel Design of Weighted Multi-Dimensional Scaling for Real-Time Data Analysis

    Publication Year: 2017, Page(s):10 - 17
    Cited by:  Papers (2)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (692 KB) | HTML iconHTML

    Projecting a high-dimensional dataset onto a lower dimensional space can improve the efficiency of knowledge discovery and facilitate real-time data analysis. One technique for dimension reduction, weighted multi-dimensional scaling (WMDS), approximately preserves pairwise weighted distances during the transformation; but its O(f(n)d) algorithm impedes real-time performance on large datasets. Thus... View full abstract»

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  • A Machine Learning Approach to Automatic Creation of Architecture-Sensitive Performance Heuristics

    Publication Year: 2017, Page(s):18 - 25
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (847 KB) | HTML iconHTML

    Recent interest in machine-learning based methods has produced many sophisticated models for performance modeling and optimization. These models tend to be sensitive to parameters of the underlying architecture and hence yield the highest prediction accuracy when trained on the target platform. Training a classifier, however, is a fairly involved process and requires knowledge of statistics and ma... View full abstract»

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  • Comparative Performance Modeling of Parallel Preconditioned Krylov Methods

    Publication Year: 2017, Page(s):26 - 33
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (485 KB) | HTML iconHTML

    Many scientific and engineering computations rely on the scalable solution of large sparse linear systems. Preconditioned Krylov methods are widely used and offer many algorithmic choices whose performance varies depending on the characteristics of the linear system. In previous work, we have shown that the performance of different Krylov methods at small scales can be modeled using a small number... View full abstract»

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  • Libsec: A Hardware Virtualization-Based Isolation for Shared Library

    Publication Year: 2017, Page(s):34 - 41
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (736 KB) | HTML iconHTML

    A typical application normally includes the main program and some shared libraries. The main program can arbitrarily execute the code of those shared libraries due to the coexistence in the same memory space. This feature can be used by attackers to carry out code-reuse attacks. Meanwhile, the shared libraries are shared across multiple applications, which can help attackers to simplify the proces... View full abstract»

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