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You searched for +publisher:"Virginia Tech" +contributor:("Ribbens, Calvin J."). Showing records 1 – 30 of 116 total matches.

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Virginia Tech

1. McDaniel, Brian Newsom. The CloudBrowser Web Application Framework.

Degree: MS, Computer Science, 2012, Virginia Tech

 While more and more applications are moving from the desktop to the web, users still expect their applications to behave like they did on the… (more)

Subjects/Keywords: server-centric; JavaScript; web frameworks

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APA (6th Edition):

McDaniel, B. N. (2012). The CloudBrowser Web Application Framework. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/32971

Chicago Manual of Style (16th Edition):

McDaniel, Brian Newsom. “The CloudBrowser Web Application Framework.” 2012. Masters Thesis, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/32971.

MLA Handbook (7th Edition):

McDaniel, Brian Newsom. “The CloudBrowser Web Application Framework.” 2012. Web. 16 Jun 2019.

Vancouver:

McDaniel BN. The CloudBrowser Web Application Framework. [Internet] [Masters thesis]. Virginia Tech; 2012. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/32971.

Council of Science Editors:

McDaniel BN. The CloudBrowser Web Application Framework. [Masters Thesis]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/32971


Virginia Tech

2. McFarland, Daniel James. Exploiting Malleable Parallelism on Multicore Systems.

Degree: MS, Computer Science, 2011, Virginia Tech

 As shared memory platforms continue to grow in core counts, the need for context-aware scheduling continues to grow. Context-aware scheduling takes into account characteristics of… (more)

Subjects/Keywords: Malleable; Resizable; Rigid; Thread

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APA (6th Edition):

McFarland, D. J. (2011). Exploiting Malleable Parallelism on Multicore Systems. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/33819

Chicago Manual of Style (16th Edition):

McFarland, Daniel James. “Exploiting Malleable Parallelism on Multicore Systems.” 2011. Masters Thesis, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/33819.

MLA Handbook (7th Edition):

McFarland, Daniel James. “Exploiting Malleable Parallelism on Multicore Systems.” 2011. Web. 16 Jun 2019.

Vancouver:

McFarland DJ. Exploiting Malleable Parallelism on Multicore Systems. [Internet] [Masters thesis]. Virginia Tech; 2011. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/33819.

Council of Science Editors:

McFarland DJ. Exploiting Malleable Parallelism on Multicore Systems. [Masters Thesis]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/33819


Virginia Tech

3. Braithwaite, Ryan Karl. NUMA Data-Access Bandwidth Characterization and Modeling.

Degree: MS, Computer Science and Applications, 2012, Virginia Tech

 Clusters of seemingly homogeneous compute nodes are increasingly heterogeneous within each node due to replication and distribution of node-level subsystems. This intra-node heterogeneity can adversely… (more)

Subjects/Keywords: Performance Modeling; NUMA; Benchmarking

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APA (6th Edition):

Braithwaite, R. K. (2012). NUMA Data-Access Bandwidth Characterization and Modeling. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/31151

Chicago Manual of Style (16th Edition):

Braithwaite, Ryan Karl. “NUMA Data-Access Bandwidth Characterization and Modeling.” 2012. Masters Thesis, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/31151.

MLA Handbook (7th Edition):

Braithwaite, Ryan Karl. “NUMA Data-Access Bandwidth Characterization and Modeling.” 2012. Web. 16 Jun 2019.

Vancouver:

Braithwaite RK. NUMA Data-Access Bandwidth Characterization and Modeling. [Internet] [Masters thesis]. Virginia Tech; 2012. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/31151.

Council of Science Editors:

Braithwaite RK. NUMA Data-Access Bandwidth Characterization and Modeling. [Masters Thesis]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/31151


Virginia Tech

4. Ringenbach, Michael. Collecting Student Data for Accreditation Assessment.

Degree: MS, Computer Science, 2011, Virginia Tech

 This paper seeks to identify one of the key problems faced by academic institutions seeking accreditation. The accreditation process requires academic institutions to conduct a… (more)

Subjects/Keywords: accreditation; assessment; Web-CAT

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APA (6th Edition):

Ringenbach, M. (2011). Collecting Student Data for Accreditation Assessment. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/31209

Chicago Manual of Style (16th Edition):

Ringenbach, Michael. “Collecting Student Data for Accreditation Assessment.” 2011. Masters Thesis, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/31209.

MLA Handbook (7th Edition):

Ringenbach, Michael. “Collecting Student Data for Accreditation Assessment.” 2011. Web. 16 Jun 2019.

Vancouver:

Ringenbach M. Collecting Student Data for Accreditation Assessment. [Internet] [Masters thesis]. Virginia Tech; 2011. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/31209.

Council of Science Editors:

Ringenbach M. Collecting Student Data for Accreditation Assessment. [Masters Thesis]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/31209


Virginia Tech

5. Banerjee, Shankha. MPIOR: A Framework to Analyze File System Performance of MPI Applications.

Degree: MS, Computer Science and Applications, 2012, Virginia Tech

 MPI I/O replay (MPIOR) is an I/O performance modeling and prediction tool used to trace and replay a parallel application to determine application performance under… (more)

Subjects/Keywords: I/O; replay; MPI; trace

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APA (6th Edition):

Banerjee, S. (2012). MPIOR: A Framework to Analyze File System Performance of MPI Applications. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/31484

Chicago Manual of Style (16th Edition):

Banerjee, Shankha. “MPIOR: A Framework to Analyze File System Performance of MPI Applications.” 2012. Masters Thesis, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/31484.

MLA Handbook (7th Edition):

Banerjee, Shankha. “MPIOR: A Framework to Analyze File System Performance of MPI Applications.” 2012. Web. 16 Jun 2019.

Vancouver:

Banerjee S. MPIOR: A Framework to Analyze File System Performance of MPI Applications. [Internet] [Masters thesis]. Virginia Tech; 2012. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/31484.

Council of Science Editors:

Banerjee S. MPIOR: A Framework to Analyze File System Performance of MPI Applications. [Masters Thesis]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/31484


Virginia Tech

6. Mahendiran, Aravindan. Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics.

Degree: MS, Computer Science, 2014, Virginia Tech

 Twitter has become a popular data source in the recent decade and garnered a significant amount of attention as a surrogate data source for many… (more)

Subjects/Keywords: Election Forecasting; Twitter; Query Expansion; Social Group Modeling; Probabilistic Soft Logic

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APA (6th Edition):

Mahendiran, A. (2014). Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/25430

Chicago Manual of Style (16th Edition):

Mahendiran, Aravindan. “Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics.” 2014. Masters Thesis, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/25430.

MLA Handbook (7th Edition):

Mahendiran, Aravindan. “Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics.” 2014. Web. 16 Jun 2019.

Vancouver:

Mahendiran A. Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics. [Internet] [Masters thesis]. Virginia Tech; 2014. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/25430.

Council of Science Editors:

Mahendiran A. Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics. [Masters Thesis]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/25430


Virginia Tech

7. Belgin, Mehmet. Structure-based Optimizations for Sparse Matrix-Vector Multiply.

Degree: PhD, Computer Science, 2010, Virginia Tech

 This dissertation introduces two novel techniques, OSF and PBR, to improve the performance of Sparse Matrix-vector Multiply (SMVM) kernels, which dominate the runtime of iterative… (more)

Subjects/Keywords: Code Generators; Vectorization; Sparse; SpMV; SMVM; Matrix Vector Multiply; PBR; OSF; thread pool; parallel SpMV

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APA (6th Edition):

Belgin, M. (2010). Structure-based Optimizations for Sparse Matrix-Vector Multiply. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/30260

Chicago Manual of Style (16th Edition):

Belgin, Mehmet. “Structure-based Optimizations for Sparse Matrix-Vector Multiply.” 2010. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/30260.

MLA Handbook (7th Edition):

Belgin, Mehmet. “Structure-based Optimizations for Sparse Matrix-Vector Multiply.” 2010. Web. 16 Jun 2019.

Vancouver:

Belgin M. Structure-based Optimizations for Sparse Matrix-Vector Multiply. [Internet] [Doctoral dissertation]. Virginia Tech; 2010. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/30260.

Council of Science Editors:

Belgin M. Structure-based Optimizations for Sparse Matrix-Vector Multiply. [Doctoral Dissertation]. Virginia Tech; 2010. Available from: http://hdl.handle.net/10919/30260


Virginia Tech

8. Tranquilli, Paul J. Lightly-Implicit Methods for the Time Integration of Large Applications.

Degree: PhD, Computer Science, 2016, Virginia Tech

 Many scientific and engineering applications require the solution of large systems of initial value problems arising from method of lines discretization of partial differential equations.… (more)

Subjects/Keywords: Time Integration; Numerical PDEs; Numerical ODEs

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APA (6th Edition):

Tranquilli, P. J. (2016). Lightly-Implicit Methods for the Time Integration of Large Applications. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/81974

Chicago Manual of Style (16th Edition):

Tranquilli, Paul J. “Lightly-Implicit Methods for the Time Integration of Large Applications.” 2016. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/81974.

MLA Handbook (7th Edition):

Tranquilli, Paul J. “Lightly-Implicit Methods for the Time Integration of Large Applications.” 2016. Web. 16 Jun 2019.

Vancouver:

Tranquilli PJ. Lightly-Implicit Methods for the Time Integration of Large Applications. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/81974.

Council of Science Editors:

Tranquilli PJ. Lightly-Implicit Methods for the Time Integration of Large Applications. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/81974


Virginia Tech

9. Zavar Moosavi, Azam Sadat. Probabilistic and Statistical Learning Models for Error Modeling and Uncertainty Quantification.

Degree: PhD, Computer Science, 2018, Virginia Tech

 Simulations and modeling of large-scale systems are vital to understanding real world phenomena. However, even advanced numerical models can only approximate the true physics. The… (more)

Subjects/Keywords: Uncertainty Quantification; Uncertainty Reduction; Stochastic Simulation of Chemical Reactions; Reduced-Order Models; Structural Uncertainty; Data Assimilation; Numerical Weather Prediction Models; Machine Learning

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APA (6th Edition):

Zavar Moosavi, A. S. (2018). Probabilistic and Statistical Learning Models for Error Modeling and Uncertainty Quantification. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/82491

Chicago Manual of Style (16th Edition):

Zavar Moosavi, Azam Sadat. “Probabilistic and Statistical Learning Models for Error Modeling and Uncertainty Quantification.” 2018. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/82491.

MLA Handbook (7th Edition):

Zavar Moosavi, Azam Sadat. “Probabilistic and Statistical Learning Models for Error Modeling and Uncertainty Quantification.” 2018. Web. 16 Jun 2019.

Vancouver:

Zavar Moosavi AS. Probabilistic and Statistical Learning Models for Error Modeling and Uncertainty Quantification. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/82491.

Council of Science Editors:

Zavar Moosavi AS. Probabilistic and Statistical Learning Models for Error Modeling and Uncertainty Quantification. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/82491


Virginia Tech

10. Krishnan, Siddharth. Seeing the Forest for the Trees: New approaches to Characterizing and Forecasting Cascades.

Degree: PhD, Computer Science, 2018, Virginia Tech

 Cascades are a popular construct to observe and study information propagation (or diffusion) in social media such as Twitter and are defined using notions of… (more)

Subjects/Keywords: Information cascades; Forecasting

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APA (6th Edition):

Krishnan, S. (2018). Seeing the Forest for the Trees: New approaches to Characterizing and Forecasting Cascades. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/83362

Chicago Manual of Style (16th Edition):

Krishnan, Siddharth. “Seeing the Forest for the Trees: New approaches to Characterizing and Forecasting Cascades.” 2018. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/83362.

MLA Handbook (7th Edition):

Krishnan, Siddharth. “Seeing the Forest for the Trees: New approaches to Characterizing and Forecasting Cascades.” 2018. Web. 16 Jun 2019.

Vancouver:

Krishnan S. Seeing the Forest for the Trees: New approaches to Characterizing and Forecasting Cascades. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/83362.

Council of Science Editors:

Krishnan S. Seeing the Forest for the Trees: New approaches to Characterizing and Forecasting Cascades. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/83362


Virginia Tech

11. Hou, Kaixi. Exploring Performance Portability for Accelerators via High-level Parallel Patterns.

Degree: PhD, Computer Science, 2018, Virginia Tech

 Nowadays, parallel accelerators have become prominent and ubiquitous, e.g., multi-core CPUs, many-core GPUs (Graphics Processing Units) and Intel Xeon Phi. The performance gains from them… (more)

Subjects/Keywords: GPU; AVX; sort; stencil; wavefront; pattern; parallelism

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APA (6th Edition):

Hou, K. (2018). Exploring Performance Portability for Accelerators via High-level Parallel Patterns. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/84923

Chicago Manual of Style (16th Edition):

Hou, Kaixi. “Exploring Performance Portability for Accelerators via High-level Parallel Patterns.” 2018. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/84923.

MLA Handbook (7th Edition):

Hou, Kaixi. “Exploring Performance Portability for Accelerators via High-level Parallel Patterns.” 2018. Web. 16 Jun 2019.

Vancouver:

Hou K. Exploring Performance Portability for Accelerators via High-level Parallel Patterns. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/84923.

Council of Science Editors:

Hou K. Exploring Performance Portability for Accelerators via High-level Parallel Patterns. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/84923


Virginia Tech

12. Yeom, Jae-seung. Optimizing Data Accesses for Scaling Data-intensive Scientific Applications.

Degree: PhD, Computer Science, 2014, Virginia Tech

 Data-intensive scientific applications often process an enormous amount of data. The scalability of such applications depends critically on how to manage the locality of data.… (more)

Subjects/Keywords: Parallel systems; Software-managed memories; Distributed memories; Data locality; Scalability; Parallel discrete event simulation; Social networks; Contagion

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APA (6th Edition):

Yeom, J. (2014). Optimizing Data Accesses for Scaling Data-intensive Scientific Applications. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/64180

Chicago Manual of Style (16th Edition):

Yeom, Jae-seung. “Optimizing Data Accesses for Scaling Data-intensive Scientific Applications.” 2014. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/64180.

MLA Handbook (7th Edition):

Yeom, Jae-seung. “Optimizing Data Accesses for Scaling Data-intensive Scientific Applications.” 2014. Web. 16 Jun 2019.

Vancouver:

Yeom J. Optimizing Data Accesses for Scaling Data-intensive Scientific Applications. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/64180.

Council of Science Editors:

Yeom J. Optimizing Data Accesses for Scaling Data-intensive Scientific Applications. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/64180


Virginia Tech

13. Nino Ruiz, Elias David. Efficient formulation and implementation of ensemble based methods in data assimilation.

Degree: PhD, Computer Science, 2016, Virginia Tech

 Ensemble-based methods have gained widespread popularity in the field of data assimilation. An ensemble of model realizations encapsulates information about the error correlations driven by… (more)

Subjects/Keywords: Ensemble-based methods; ensemble Kalman filter; ensemble square root filter; hybrid data assimilation; background error covariance matrix estimation; parallel data assimilation

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APA (6th Edition):

Nino Ruiz, E. D. (2016). Efficient formulation and implementation of ensemble based methods in data assimilation. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/64438

Chicago Manual of Style (16th Edition):

Nino Ruiz, Elias David. “Efficient formulation and implementation of ensemble based methods in data assimilation.” 2016. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/64438.

MLA Handbook (7th Edition):

Nino Ruiz, Elias David. “Efficient formulation and implementation of ensemble based methods in data assimilation.” 2016. Web. 16 Jun 2019.

Vancouver:

Nino Ruiz ED. Efficient formulation and implementation of ensemble based methods in data assimilation. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/64438.

Council of Science Editors:

Nino Ruiz ED. Efficient formulation and implementation of ensemble based methods in data assimilation. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/64438


Virginia Tech

14. Linford, John Christian. Accelerating Atmospheric Modeling Through Emerging Multi-core Technologies.

Degree: PhD, Computer Science, 2010, Virginia Tech

 The new generations of multi-core chipset architectures achieve unprecedented levels of computational power while respecting physical and economical constraints. The cost of this power is… (more)

Subjects/Keywords: hardware; high performance computing; software

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APA (6th Edition):

Linford, J. C. (2010). Accelerating Atmospheric Modeling Through Emerging Multi-core Technologies. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/27599

Chicago Manual of Style (16th Edition):

Linford, John Christian. “Accelerating Atmospheric Modeling Through Emerging Multi-core Technologies.” 2010. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/27599.

MLA Handbook (7th Edition):

Linford, John Christian. “Accelerating Atmospheric Modeling Through Emerging Multi-core Technologies.” 2010. Web. 16 Jun 2019.

Vancouver:

Linford JC. Accelerating Atmospheric Modeling Through Emerging Multi-core Technologies. [Internet] [Doctoral dissertation]. Virginia Tech; 2010. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/27599.

Council of Science Editors:

Linford JC. Accelerating Atmospheric Modeling Through Emerging Multi-core Technologies. [Doctoral Dissertation]. Virginia Tech; 2010. Available from: http://hdl.handle.net/10919/27599


Virginia Tech

15. Kang, Pilsung. Modular Implementation of Program Adaptation with Existing Scientific Codes.

Degree: PhD, Computer Science, 2010, Virginia Tech

 Often times, scientific software needs to be adapted for different execution environments, problem sets, and available resources to ensure its efficiency and reliability. Directly modifying… (more)

Subjects/Keywords: scientic computing; parallel programming; program adaptation

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APA (6th Edition):

Kang, P. (2010). Modular Implementation of Program Adaptation with Existing Scientific Codes. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28783

Chicago Manual of Style (16th Edition):

Kang, Pilsung. “Modular Implementation of Program Adaptation with Existing Scientific Codes.” 2010. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/28783.

MLA Handbook (7th Edition):

Kang, Pilsung. “Modular Implementation of Program Adaptation with Existing Scientific Codes.” 2010. Web. 16 Jun 2019.

Vancouver:

Kang P. Modular Implementation of Program Adaptation with Existing Scientific Codes. [Internet] [Doctoral dissertation]. Virginia Tech; 2010. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/28783.

Council of Science Editors:

Kang P. Modular Implementation of Program Adaptation with Existing Scientific Codes. [Doctoral Dissertation]. Virginia Tech; 2010. Available from: http://hdl.handle.net/10919/28783


Virginia Tech

16. Pugaonkar, Aniket Narayan. A High Performance C++ Generic Benchmark for Computational Epidemiology.

Degree: MS, Computer Science, 2015, Virginia Tech

 An effective tool used by planners and policy makers in public health, such as Center for Disease Control (CDC), to curtail spread of infectious diseases… (more)

Subjects/Keywords: Benchmark; Epidemiology; EpiSimdemics; EpiFast; C++11; BOOST C++ libraries; Intel TBB; Intel Cilk Plus; Intel MIC

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APA (6th Edition):

Pugaonkar, A. N. (2015). A High Performance C++ Generic Benchmark for Computational Epidemiology. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/51243

Chicago Manual of Style (16th Edition):

Pugaonkar, Aniket Narayan. “A High Performance C++ Generic Benchmark for Computational Epidemiology.” 2015. Masters Thesis, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/51243.

MLA Handbook (7th Edition):

Pugaonkar, Aniket Narayan. “A High Performance C++ Generic Benchmark for Computational Epidemiology.” 2015. Web. 16 Jun 2019.

Vancouver:

Pugaonkar AN. A High Performance C++ Generic Benchmark for Computational Epidemiology. [Internet] [Masters thesis]. Virginia Tech; 2015. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/51243.

Council of Science Editors:

Pugaonkar AN. A High Performance C++ Generic Benchmark for Computational Epidemiology. [Masters Thesis]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/51243

17. Hamid, Tania. On the Feasibility of MapReduce to Compute Phase Space Properties of Graphical Dynamical Systems: An Empirical Study.

Degree: MS, Computer Science, 2015, Virginia Tech

 A graph dynamical system (GDS) is a theoretical construct that can be used to simulate and analyze the dynamics of a wide spectrum of real… (more)

Subjects/Keywords: Graph Dynamical Systems; GDS; MapReduce; Map; Reduce; Hadoop

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APA (6th Edition):

Hamid, T. (2015). On the Feasibility of MapReduce to Compute Phase Space Properties of Graphical Dynamical Systems: An Empirical Study. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/54546

Chicago Manual of Style (16th Edition):

Hamid, Tania. “On the Feasibility of MapReduce to Compute Phase Space Properties of Graphical Dynamical Systems: An Empirical Study.” 2015. Masters Thesis, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/54546.

MLA Handbook (7th Edition):

Hamid, Tania. “On the Feasibility of MapReduce to Compute Phase Space Properties of Graphical Dynamical Systems: An Empirical Study.” 2015. Web. 16 Jun 2019.

Vancouver:

Hamid T. On the Feasibility of MapReduce to Compute Phase Space Properties of Graphical Dynamical Systems: An Empirical Study. [Internet] [Masters thesis]. Virginia Tech; 2015. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/54546.

Council of Science Editors:

Hamid T. On the Feasibility of MapReduce to Compute Phase Space Properties of Graphical Dynamical Systems: An Empirical Study. [Masters Thesis]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/54546


Virginia Tech

18. Arendt, Dustin Lockhart. In Search of Self-Organization.

Degree: PhD, Computer Science and Applications, 2012, Virginia Tech

 Many who study complex systems believe that the complexity we observe in the world around us is frequently the product of a large number of… (more)

Subjects/Keywords: Dimer Automata; Self-Organization; GPGPU; Complex Systems

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APA (6th Edition):

Arendt, D. L. (2012). In Search of Self-Organization. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/26465

Chicago Manual of Style (16th Edition):

Arendt, Dustin Lockhart. “In Search of Self-Organization.” 2012. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/26465.

MLA Handbook (7th Edition):

Arendt, Dustin Lockhart. “In Search of Self-Organization.” 2012. Web. 16 Jun 2019.

Vancouver:

Arendt DL. In Search of Self-Organization. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/26465.

Council of Science Editors:

Arendt DL. In Search of Self-Organization. [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/26465

19. Attia, Ahmed Mohamed Mohamed. Advanced Sampling Methods for Solving Large-Scale Inverse Problems.

Degree: PhD, Computer Science, 2016, Virginia Tech

 Ensemble and variational techniques have gained wide popularity as the two main approaches for solving data assimilation and inverse problems. The majority of the methods… (more)

Subjects/Keywords: Data Assimilation; Inverse Problems; Uncertainty Quantification; Hamiltonian Monte-Carlo; Cluster Sampling Filters; High Performance Computing.

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APA (6th Edition):

Attia, A. M. M. (2016). Advanced Sampling Methods for Solving Large-Scale Inverse Problems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/73683

Chicago Manual of Style (16th Edition):

Attia, Ahmed Mohamed Mohamed. “Advanced Sampling Methods for Solving Large-Scale Inverse Problems.” 2016. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/73683.

MLA Handbook (7th Edition):

Attia, Ahmed Mohamed Mohamed. “Advanced Sampling Methods for Solving Large-Scale Inverse Problems.” 2016. Web. 16 Jun 2019.

Vancouver:

Attia AMM. Advanced Sampling Methods for Solving Large-Scale Inverse Problems. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/73683.

Council of Science Editors:

Attia AMM. Advanced Sampling Methods for Solving Large-Scale Inverse Problems. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/73683


Virginia Tech

20. Hebbur Venkata Subba Rao, Vishwas. Adjoint based solution and uncertainty quantification techniques for variational inverse problems.

Degree: PhD, Computer Science, 2015, Virginia Tech

 Variational inverse problems integrate computational simulations of physical phenomena with physical measurements in an informational feedback control system. Control parameters of the computational model are… (more)

Subjects/Keywords: Data assimilation; Inverse problems; sensitivity analysis

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Hebbur Venkata Subba Rao, V. (2015). Adjoint based solution and uncertainty quantification techniques for variational inverse problems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/76665

Chicago Manual of Style (16th Edition):

Hebbur Venkata Subba Rao, Vishwas. “Adjoint based solution and uncertainty quantification techniques for variational inverse problems.” 2015. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/76665.

MLA Handbook (7th Edition):

Hebbur Venkata Subba Rao, Vishwas. “Adjoint based solution and uncertainty quantification techniques for variational inverse problems.” 2015. Web. 16 Jun 2019.

Vancouver:

Hebbur Venkata Subba Rao V. Adjoint based solution and uncertainty quantification techniques for variational inverse problems. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/76665.

Council of Science Editors:

Hebbur Venkata Subba Rao V. Adjoint based solution and uncertainty quantification techniques for variational inverse problems. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/76665


Virginia Tech

21. Cheng, Yue. Workload-aware Efficient Storage Systems.

Degree: PhD, Computer Science, 2017, Virginia Tech

 The growing disparity in data storage and retrieval needs of modern applications is driving the proliferation of a wide variety of storage systems (e.g., key-value… (more)

Subjects/Keywords: Storage Systems; Cloud Computing; Data Management; Key-Value Stores; Object Stores; Flash SSDs; Efficiency; Flexibility

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APA (6th Edition):

Cheng, Y. (2017). Workload-aware Efficient Storage Systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/78677

Chicago Manual of Style (16th Edition):

Cheng, Yue. “Workload-aware Efficient Storage Systems.” 2017. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/78677.

MLA Handbook (7th Edition):

Cheng, Yue. “Workload-aware Efficient Storage Systems.” 2017. Web. 16 Jun 2019.

Vancouver:

Cheng Y. Workload-aware Efficient Storage Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2017. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/78677.

Council of Science Editors:

Cheng Y. Workload-aware Efficient Storage Systems. [Doctoral Dissertation]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/78677


Virginia Tech

22. Li, Min. A resource management framework for cloud computing.

Degree: PhD, Computer Science, 2014, Virginia Tech

 The cloud computing paradigm is realized through large scale distributed resource management and computation platforms such as MapReduce, Hadoop, Dryad, and Pregel. These platforms enable… (more)

Subjects/Keywords: Cloud Computing; MapReduce; Virtual Desktop Environment; Resource Management; I/O Reduction

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APA (6th Edition):

Li, M. (2014). A resource management framework for cloud computing. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/47804

Chicago Manual of Style (16th Edition):

Li, Min. “A resource management framework for cloud computing.” 2014. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/47804.

MLA Handbook (7th Edition):

Li, Min. “A resource management framework for cloud computing.” 2014. Web. 16 Jun 2019.

Vancouver:

Li M. A resource management framework for cloud computing. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/47804.

Council of Science Editors:

Li M. A resource management framework for cloud computing. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/47804


Virginia Tech

23. Cioaca, Alexandru George. A Computational Framework for Assessing and Optimizing the Performance of Observational Networks in 4D-Var Data Assimilation.

Degree: PhD, Computer Science, 2013, Virginia Tech

 A deep scientific understanding of complex physical systems, such as the atmosphere, can be achieved neither by direct measurements nor by numerical simulations alone. Data… (more)

Subjects/Keywords: data assimilation; dynamic data-driven problem; second-order adjoints; adaptive observations; sensor placement; intelligent sensors; sensitivity analysis; uncertainty quantification; nonlinear optimization; inverse problems; parameter estimation; matrix-free linear solvers; truncated singular value decomposition

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APA (6th Edition):

Cioaca, A. G. (2013). A Computational Framework for Assessing and Optimizing the Performance of Observational Networks in 4D-Var Data Assimilation. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/51795

Chicago Manual of Style (16th Edition):

Cioaca, Alexandru George. “A Computational Framework for Assessing and Optimizing the Performance of Observational Networks in 4D-Var Data Assimilation.” 2013. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/51795.

MLA Handbook (7th Edition):

Cioaca, Alexandru George. “A Computational Framework for Assessing and Optimizing the Performance of Observational Networks in 4D-Var Data Assimilation.” 2013. Web. 16 Jun 2019.

Vancouver:

Cioaca AG. A Computational Framework for Assessing and Optimizing the Performance of Observational Networks in 4D-Var Data Assimilation. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/51795.

Council of Science Editors:

Cioaca AG. A Computational Framework for Assessing and Optimizing the Performance of Observational Networks in 4D-Var Data Assimilation. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/51795


Virginia Tech

24. Aji, Ashwin M. Programming High-Performance Clusters with Heterogeneous Computing Devices.

Degree: PhD, Computer Science, 2015, Virginia Tech

 Today's high-performance computing (HPC) clusters are seeing an increase in the adoption of accelerators like GPUs, FPGAs and co-processors, leading to heterogeneity in the computation… (more)

Subjects/Keywords: Runtime Systems; Programming Models; General Purpose Graphics Processing Units (GPGPUs); Message Passing Interface (MPI); CUDA; OpenCL

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APA (6th Edition):

Aji, A. M. (2015). Programming High-Performance Clusters with Heterogeneous Computing Devices. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/52366

Chicago Manual of Style (16th Edition):

Aji, Ashwin M. “Programming High-Performance Clusters with Heterogeneous Computing Devices.” 2015. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/52366.

MLA Handbook (7th Edition):

Aji, Ashwin M. “Programming High-Performance Clusters with Heterogeneous Computing Devices.” 2015. Web. 16 Jun 2019.

Vancouver:

Aji AM. Programming High-Performance Clusters with Heterogeneous Computing Devices. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/52366.

Council of Science Editors:

Aji AM. Programming High-Performance Clusters with Heterogeneous Computing Devices. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/52366


Virginia Tech

25. Alexe, Mihai. Adjoint-based space-time adaptive solution algorithms for sensitivity analysis and inverse problems.

Degree: PhD, Computer Science, 2011, Virginia Tech

 Adaptivity in both space and time has become the norm for solving problems modeled by partial differential equations. The size of the discretized problem makes… (more)

Subjects/Keywords: Inverse problems; Adjoint Method; Adaptive Mesh Refinement; Automatic Differentiation

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APA (6th Edition):

Alexe, M. (2011). Adjoint-based space-time adaptive solution algorithms for sensitivity analysis and inverse problems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/37515

Chicago Manual of Style (16th Edition):

Alexe, Mihai. “Adjoint-based space-time adaptive solution algorithms for sensitivity analysis and inverse problems.” 2011. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/37515.

MLA Handbook (7th Edition):

Alexe, Mihai. “Adjoint-based space-time adaptive solution algorithms for sensitivity analysis and inverse problems.” 2011. Web. 16 Jun 2019.

Vancouver:

Alexe M. Adjoint-based space-time adaptive solution algorithms for sensitivity analysis and inverse problems. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/37515.

Council of Science Editors:

Alexe M. Adjoint-based space-time adaptive solution algorithms for sensitivity analysis and inverse problems. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/37515


Virginia Tech

26. Ramesh, Bharath. Samhita: Virtual Shared Memory for Non-Cache-Coherent Systems.

Degree: PhD, Computer Science, 2013, Virginia Tech

 Among the key challenges of computing today are the emergence of many-core architectures and the resulting need to effectively exploit explicit parallelism. Indeed, programmers are… (more)

Subjects/Keywords: Distributed Shared Memory; Virtual Shared Memory; Memory Consistency

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APA (6th Edition):

Ramesh, B. (2013). Samhita: Virtual Shared Memory for Non-Cache-Coherent Systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/23687

Chicago Manual of Style (16th Edition):

Ramesh, Bharath. “Samhita: Virtual Shared Memory for Non-Cache-Coherent Systems.” 2013. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/23687.

MLA Handbook (7th Edition):

Ramesh, Bharath. “Samhita: Virtual Shared Memory for Non-Cache-Coherent Systems.” 2013. Web. 16 Jun 2019.

Vancouver:

Ramesh B. Samhita: Virtual Shared Memory for Non-Cache-Coherent Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/23687.

Council of Science Editors:

Ramesh B. Samhita: Virtual Shared Memory for Non-Cache-Coherent Systems. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/23687


Virginia Tech

27. Mehmood, Arshad. Active/Passive Controls and Energy Harvesting from Vortex-Induced Vibrations.

Degree: PhD, Engineering Science and Mechanics, 2013, Virginia Tech

 Fluid-structure interactions occur in many enginnering and industrial applications. Such interactions may result in undesirable forces acting on the structure that may cause fatigue and… (more)

Subjects/Keywords: Vortex-induced vibrations; Actice/Passive controls; Nonlinear energy sink; Rotary oscillations; Inline oscillations; Energy harvesting

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APA (6th Edition):

Mehmood, A. (2013). Active/Passive Controls and Energy Harvesting from Vortex-Induced Vibrations. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/23902

Chicago Manual of Style (16th Edition):

Mehmood, Arshad. “Active/Passive Controls and Energy Harvesting from Vortex-Induced Vibrations.” 2013. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/23902.

MLA Handbook (7th Edition):

Mehmood, Arshad. “Active/Passive Controls and Energy Harvesting from Vortex-Induced Vibrations.” 2013. Web. 16 Jun 2019.

Vancouver:

Mehmood A. Active/Passive Controls and Energy Harvesting from Vortex-Induced Vibrations. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/23902.

Council of Science Editors:

Mehmood A. Active/Passive Controls and Energy Harvesting from Vortex-Induced Vibrations. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/23902


Virginia Tech

28. Xu, Luna. A Workload-aware Resource Management and Scheduling System for Big Data Analysis.

Degree: PhD, Computer Science, 2019, Virginia Tech

 The big data era has driven the needs for data analysis in every aspect of our daily lives. With the rapid growth of data size… (more)

Subjects/Keywords: resource management; big data; scheduling; heterogeneity

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APA (6th Edition):

Xu, L. (2019). A Workload-aware Resource Management and Scheduling System for Big Data Analysis. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/87469

Chicago Manual of Style (16th Edition):

Xu, Luna. “A Workload-aware Resource Management and Scheduling System for Big Data Analysis.” 2019. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/87469.

MLA Handbook (7th Edition):

Xu, Luna. “A Workload-aware Resource Management and Scheduling System for Big Data Analysis.” 2019. Web. 16 Jun 2019.

Vancouver:

Xu L. A Workload-aware Resource Management and Scheduling System for Big Data Analysis. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/87469.

Council of Science Editors:

Xu L. A Workload-aware Resource Management and Scheduling System for Big Data Analysis. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/87469


Virginia Tech

29. Pyla, Hari Krishna. Safe Concurrent Programming and Execution.

Degree: PhD, Computer Science, 2013, Virginia Tech

 The increasing prevalence of multi and many core processors has brought the issues of concurrency and parallelism to the forefront of everyday computing. Even for… (more)

Subjects/Keywords: Concurrent Programming; Concurrency Bugs; Program Analysis; Runtime Systems; Deadlock Detection and Recovery; Speculative Parall

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APA (6th Edition):

Pyla, H. K. (2013). Safe Concurrent Programming and Execution. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/19276

Chicago Manual of Style (16th Edition):

Pyla, Hari Krishna. “Safe Concurrent Programming and Execution.” 2013. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/19276.

MLA Handbook (7th Edition):

Pyla, Hari Krishna. “Safe Concurrent Programming and Execution.” 2013. Web. 16 Jun 2019.

Vancouver:

Pyla HK. Safe Concurrent Programming and Execution. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/19276.

Council of Science Editors:

Pyla HK. Safe Concurrent Programming and Execution. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/19276


Virginia Tech

30. Schneider, Scott. Shared Memory Abstractions for Heterogeneous Multicore Processors.

Degree: PhD, Computer Science, 2010, Virginia Tech

 We are now seeing diminishing returns from classic single-core processor designs, yet the number of transistors available for a processor is still increasing. Processor architects… (more)

Subjects/Keywords: Parallel Programming; EMM; Cell BE; Programming Models; Parallel Hardware Architecture

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APA (6th Edition):

Schneider, S. (2010). Shared Memory Abstractions for Heterogeneous Multicore Processors. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/30240

Chicago Manual of Style (16th Edition):

Schneider, Scott. “Shared Memory Abstractions for Heterogeneous Multicore Processors.” 2010. Doctoral Dissertation, Virginia Tech. Accessed June 16, 2019. http://hdl.handle.net/10919/30240.

MLA Handbook (7th Edition):

Schneider, Scott. “Shared Memory Abstractions for Heterogeneous Multicore Processors.” 2010. Web. 16 Jun 2019.

Vancouver:

Schneider S. Shared Memory Abstractions for Heterogeneous Multicore Processors. [Internet] [Doctoral dissertation]. Virginia Tech; 2010. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10919/30240.

Council of Science Editors:

Schneider S. Shared Memory Abstractions for Heterogeneous Multicore Processors. [Doctoral Dissertation]. Virginia Tech; 2010. Available from: http://hdl.handle.net/10919/30240

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