Computer Science Technical Reports

 

The Department of Computer Science collection of technical reports began in 1973. Please use the subject headings listed below for all submissions.

Subject Headings:
  • Algorithms
  • Big Data
  • Bioinformatics
  • Computational Biology
  • Computational Science and Engineering
  • Computer Graphics/Animation
  • Computer Science Education
  • Computer Systems
  • Cyberarts
  • Cybersecurity
  • Data and Text Mining
  • Digital Education
  • Digital Libraries
  • Discrete Event Simulation
  • High Performance Computing
  • Human Computer Interaction
  • Information Retrieval
  • Machine Learning
  • Mathematical Programming
  • Mathematical Software
  • Modeling and Simulation
  • Networking
  • Numerical Analysis
  • Parallel and Distributed Computing
  • Problem Solving Environments
  • Software Engineering
  • Theoretical Computer Science
  • Virtual/Augmented Reality
  • Visualization

Recent Submissions

  • Visualize This: Lessons from the Front-lines of High Performance Visualization 

    Mohammed, Ayat; Polys, Nicholas F.; Farrah, Duncan (Department of Computer Science, Virginia Polytechnic Institute & State University, 2020-04-02), TR-20-01
    This paper presents a comprehensive workflow to address two major factors in multivariate multidimensional (MVMD) scientific visualization: the scalability of rendering and the scalability of representation (for perception). ...

  • Compiler-Directed Failure Atomicity for Nonvolatile Memory 

    Liu, Qingrui; Izraelevitz, Joseph; Lee, Se Kwon; Scott, Michael L.; Noh, Sam H.; Jung, Changhee (Department of Computer Science, Virginia Polytechnic Institute & State University, 2019-07-15), TR-19-02
    This paper presents iDO, a compiler-directed approach to failure atomicity with nonvolatile memory. Unlike most prior work, which instruments each store of persistent data for redo or undo logging, the iDO compiler identifies ...

  • ELASTIN: Achieving Stagnation-Free Intermittent Computation with Boundary-Free Adaptive Execution 

    Choi, Jongouk; Joe, Hyunwoo; Kim, Yongjoo; Jung, Changhee (Department of Computer Science, Virginia Polytechnic Institute & State University, 2019-07-15), TR-19-01
    This paper presents ELASTIN, a stagnation-free intermittent computing system for energy-harvesting devices that ensures forward progress in the presence of frequent power outages without partitioning program into recoverable ...

  • BenchPrime: Accurate Benchmark Subsetting with Optimized Clustering Algorithm Selection 

    Liu, Qingrui; Wu, Xiaolong; Kittinger, Larry; Levy, Markus; Jung, Changhee (Department of Computer Science, Virginia Polytechnic Institute & State University, 2018-08-24), TR-18-06
    This paper presents BenchPrime, an automated benchmark analysis toolset that is systematic and extensible to analyze the similarity and diversity of benchmark suites. BenchPrime takes multiple benchmark suites and their ...

  • A Composable Workflow for Productive FPGA Computing via Whole-Program Analysis and Transformation (with Code Excerpts) 

    Sathre, Paul; Helal, Ahmed E.; Feng, Wu-chun (Department of Computer Science, Virginia Polytechnic Institute & State University, 2018-07-24), TR-18-05
    We present a composable workflow to enable highly-productive heterogeneous computing on FPGAs. The workflow consists of a trio of static analysis and transformation tools: (1) a whole-program, source-to-source translator ...

  • MOANA: Modeling and Analyzing I/O Variability in Parallel System Experimental Design 

    Cameron, Kirk W.; Anwar, Ali; Cheng, Yue; Xu, Li; Li, Bo; Ananth, Uday; Lux, Thomas; Hong, Yili; Watson, Layne T.; Butt, Ali R. (Department of Computer Science, Virginia Polytechnic Institute & State University, 2018-04-19), TR-18-04
    Exponential increases in complexity and scale make variability a growing threat to sustaining HPC performance at exascale. Performance variability in HPC I/O is common, acute, and formidable. We take the first step towards ...

  • Modeling Influence using Weak Supervision: A joint Link and Post-level Analysis 

    Chen, Liangzhe; Prakash, B. Aditya (Department of Computer Science, Virginia Polytechnic Institute & State University, 2018-04-09), TR-18-03
    Microblogging websites, like Twitter and Weibo, are used by billions of people to create and spread information. This activity depends on various factors such as the friendship links between users, their topic interests ...

  • Segmentations with Explanations for Outage Analysis 

    Chen, Liangzhe; Muralidhar, Nikhil; Chinthavali, Supriya; Ramakrishnan, Naren; Prakash, B. Aditya (Department of Computer Science, Virginia Polytechnic Institute & State University, 2018-04-09), TR-18-02
    Recent hurricane events have caused unprecedented amounts of damage and severely threatened our public safety and economy. The most observable (and severe) impact of these hurricanes is the loss of electric power in many ...

  • GPU Power Prediction via Ensemble Machine Learning for DVFS Space Exploration 

    Dutta, Bishwajit; Adhinarayanan, Vignesh; Feng, Wu-chun (Department of Computer Science, Virginia Polytechnic Institute & State University, 2018-02-02), TR-18-01
    A software-based approach to achieve high performance within a power budget often involves dynamic voltage and frequency scaling (DVFS). Consequently, accurately predicting the power consumption of an application at different ...

  • ETH: A Framework for the Design-Space Exploration of Extreme-Scale Visualization 

    Abrams, Gregory; Adhinarayanan, Vignesh; Feng, Wu-chun; Rogers, David; Ahrens, Jams; Wilson, Luke (Department of Computer Science, Virginia Polytechnic Institute & State University, 2017-09-29), TR-17-05
    As high-performance computing (HPC) moves towards the exascale era, large-scale scientific simulations are generating enormous datasets. A variety of techniques (e.g., in-situ methods, data sampling, and compression) have ...

  • CommAnalyzer: Automated Estimation of Communication Cost on HPC Clusters Using Sequential Code 

    Helal, Ahmed E.; Jung, Changhee; Feng, Wu-chun; Hanafy, Yasser Y. (Department of Computer Science, Virginia Polytechnic Institute & State University, 2017-08-14), TR-17-04
    MPI+X is the de facto standard for programming applications on HPC clusters. The performance and scalability on such systems is limited by the communication cost on different number of processes and compute nodes. Therefore, ...

  • Personal Reflections on 50 Years of Scientific Computing: 1967–2017 

    Watson, Layne T. (Department of Computer Science, Virginia Polytechnic Institute & State University, 2017-08-10), TR-17-03
    Computer hardware, software, numerical algorithms, and science and engineering applications are traced for a half century from the author's perspective.

  • Understanding Recurring Software Quality Problems of Novice Programmers 

    Techapalokul, Peeratham; Tilevich, Eli (Department of Computer Science, Virginia Polytechnic Institute & State University, 2017-07-12), TR-17-02
    It remains unclear when is the right time to introduce software quality into the computing curriculum. Introductory students often cannot afford to also worry about software quality, while advanced students may have been ...

  • DroidCat: Unified Dynamic Detection of Android Malware 

    Cai, Haipeng; Meng, Na; Ryder, Barbara G.; Yao, Danfeng (Daphne) (Department of Computer Science, Virginia Polytechnic Institute & State University, 2016), TR-17-01
    Various dynamic approaches have been developed to detect or categorize Android malware. These approaches execute software, collect call traces, and then detect abnormal system calls or sensitive API usage. Consequently, ...

  • A Numerical Investigation of Matrix-Free Implicit Time-Stepping Methods for Large CFD Simulations 

    Sarshar, Arash; Tranquilli, Paul; Pickering, Brent P.; McCall, Andrew; Sandu, Adrian; Roy, Christopher J. (2016)
    This paper is concerned with the development and testing of advanced time-stepping methods suited for the integration of time-accurate, real-world applications of computational fluid dynamics (CFD). The performance of ...

  • LIRK-W: Linearly-implicit Runge-Kutta methods with approximate matrix factorization 

    Tranquilli, Paul; Sandu, Adrian; Zhang, H. (2016-11-22)
    This paper develops a new class of linearly implicit time integration schemes called Linearly-Implicit Runge-Kutta-W (LIRK-W) methods. These schemes are based on an implicit-explicit approach which does not require a ...

  • Multivariate predictions of local reduced-order-model errors and dimensions 

    Moosavi, Azam; Stefanescu, Razvan; Sandu, Adrian (2017-01-16)
    This paper introduces multivariate input-output models to predict the errors and bases dimensions of local parametric Proper Orthogonal Decomposition reduced-order models. We refer to these multivariate mappings as the ...

  • AutoMatch: Automated Matching of Compute Kernels to Heterogeneous HPC Architectures 

    Helal, Ahmed E.; Feng, Wu-chun; Jung, Changhee; Hanafy, Yasser Y. (Department of Computer Science, Virginia Polytechnic Institute & State University, 2016-12-13), TR-16-06
    HPC systems contain a wide variety of heterogeneous computing resources, ranging from general-purpose CPUs to specialized accelerators. Porting sequential applications to such systems for achieving high performance requires ...

  • Understanding Application Behaviours for Android Security: A Systematic Characterization 

    Cai, Haipeng; Ryder, Barbara G. (Department of Computer Science, Virginia Polytechnic Institute & State University, 2016), TR-16-05
    In contrast to most existing research on Android focusing on specific security issues, there is little broad understanding of Android application run-time characteristics and their security implications. To mitigate this ...

  • Accelerating Workloads on FPGAs via OpenCL: A Case Study with OpenDwarfs 

    Verma, Anshuman; Helal, Ahmed E.; Krommydas, Konstantinos; Feng, Wu-chun (Department of Computer Science, Virginia Polytechnic Institute & State University, 2016-05-13), TR-16-04
    For decades, the streaming architecture of FPGAs has delivered accelerated performance across many application domains, such as option pricing solvers in finance, computational fluid dynamics in oil and gas, and packet ...

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