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You searched for +publisher:"Georgia Tech" +contributor:("Vuduc, Richard W."). Showing records 1 – 11 of 11 total matches.

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Georgia Tech

1. Tomita, Yu. Numerical and analytical studies of quantum error correction.

Degree: PhD, Computational Science and Engineering, 2014, Georgia Tech

 A reliable large-scale quantum computer, if built, can solve many real-life problems exponentially faster than the existing digital devices. The biggest obstacle to building one… (more)

Subjects/Keywords: Quantum computation

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APA (6th Edition):

Tomita, Y. (2014). Numerical and analytical studies of quantum error correction. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53468

Chicago Manual of Style (16th Edition):

Tomita, Yu. “Numerical and analytical studies of quantum error correction.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 17, 2019. http://hdl.handle.net/1853/53468.

MLA Handbook (7th Edition):

Tomita, Yu. “Numerical and analytical studies of quantum error correction.” 2014. Web. 17 Oct 2019.

Vancouver:

Tomita Y. Numerical and analytical studies of quantum error correction. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/1853/53468.

Council of Science Editors:

Tomita Y. Numerical and analytical studies of quantum error correction. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/53468


Georgia Tech

2. Hossain, Mohammad Moazzem. Voxel-based offsetting at high resolution with tunable speed and precision using hybrid dynamic trees.

Degree: PhD, Computational Science and Engineering, 2016, Georgia Tech

 In the recent years, digital manufacturing has experienced the wave of rapid prototyping through the innovation and ubiquity in 3D printing technology. While such advancement… (more)

Subjects/Keywords: GPGPU acceleration; Hybrid dynamic tree; Offset surface; Octree; High-resolution Voxel modeling; Digital manufacturing; CNC machining

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APA (6th Edition):

Hossain, M. M. (2016). Voxel-based offsetting at high resolution with tunable speed and precision using hybrid dynamic trees. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/56305

Chicago Manual of Style (16th Edition):

Hossain, Mohammad Moazzem. “Voxel-based offsetting at high resolution with tunable speed and precision using hybrid dynamic trees.” 2016. Doctoral Dissertation, Georgia Tech. Accessed October 17, 2019. http://hdl.handle.net/1853/56305.

MLA Handbook (7th Edition):

Hossain, Mohammad Moazzem. “Voxel-based offsetting at high resolution with tunable speed and precision using hybrid dynamic trees.” 2016. Web. 17 Oct 2019.

Vancouver:

Hossain MM. Voxel-based offsetting at high resolution with tunable speed and precision using hybrid dynamic trees. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/1853/56305.

Council of Science Editors:

Hossain MM. Voxel-based offsetting at high resolution with tunable speed and precision using hybrid dynamic trees. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/56305


Georgia Tech

3. Flick, Patrick. Parallel and Scalable Combinatorial String Algorithms on Distributed Memory Systems.

Degree: PhD, Computational Science and Engineering, 2019, Georgia Tech

 Methods for processing and analyzing DNA and genomic data are built upon combinatorial graph and string algorithms. The advent of high-throughput DNA sequencing is enabling… (more)

Subjects/Keywords: distributed memory; suffix array; suffix tree; enhanced suffix arrays; de bruijn graphs; distributed graphs; connected components

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APA (6th Edition):

Flick, P. (2019). Parallel and Scalable Combinatorial String Algorithms on Distributed Memory Systems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61257

Chicago Manual of Style (16th Edition):

Flick, Patrick. “Parallel and Scalable Combinatorial String Algorithms on Distributed Memory Systems.” 2019. Doctoral Dissertation, Georgia Tech. Accessed October 17, 2019. http://hdl.handle.net/1853/61257.

MLA Handbook (7th Edition):

Flick, Patrick. “Parallel and Scalable Combinatorial String Algorithms on Distributed Memory Systems.” 2019. Web. 17 Oct 2019.

Vancouver:

Flick P. Parallel and Scalable Combinatorial String Algorithms on Distributed Memory Systems. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/1853/61257.

Council of Science Editors:

Flick P. Parallel and Scalable Combinatorial String Algorithms on Distributed Memory Systems. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61257


Georgia Tech

4. Sao, Piyush kumar. Scalable and resilient sparse linear solvers.

Degree: PhD, Computational Science and Engineering, 2018, Georgia Tech

 Solving a large and sparse system of linear equations is a ubiquitous problem in scientific computing. The challenges in scaling such solvers on current and… (more)

Subjects/Keywords: Sparse linear solver; Distributed computing; Communication avoiding algorithm; Numerical linear algebra; Fault-tolerance

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APA (6th Edition):

Sao, P. k. (2018). Scalable and resilient sparse linear solvers. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60233

Chicago Manual of Style (16th Edition):

Sao, Piyush kumar. “Scalable and resilient sparse linear solvers.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 17, 2019. http://hdl.handle.net/1853/60233.

MLA Handbook (7th Edition):

Sao, Piyush kumar. “Scalable and resilient sparse linear solvers.” 2018. Web. 17 Oct 2019.

Vancouver:

Sao Pk. Scalable and resilient sparse linear solvers. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/1853/60233.

Council of Science Editors:

Sao Pk. Scalable and resilient sparse linear solvers. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/60233


Georgia Tech

5. Biswas, Aradhya. Energy efficient parallel and distributed simulation.

Degree: PhD, Computational Science and Engineering, 2019, Georgia Tech

 New challenges and opportunities emerge as computing interacts with our surroundings in unprecedented ways. One of these challenges is the energy consumed by computations and… (more)

Subjects/Keywords: Energy efficiency; Parallel computing; Distributed computing; Parallel and distributed simulation; Discrete event simulation; Energy profiling; Performance; Measurement; Synchronization algorithm; Dynamic data driven application system; Edge computing; Middleware; Queuing network simulation; Data parallel simulation; Parallel prefix computation

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APA (6th Edition):

Biswas, A. (2019). Energy efficient parallel and distributed simulation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61788

Chicago Manual of Style (16th Edition):

Biswas, Aradhya. “Energy efficient parallel and distributed simulation.” 2019. Doctoral Dissertation, Georgia Tech. Accessed October 17, 2019. http://hdl.handle.net/1853/61788.

MLA Handbook (7th Edition):

Biswas, Aradhya. “Energy efficient parallel and distributed simulation.” 2019. Web. 17 Oct 2019.

Vancouver:

Biswas A. Energy efficient parallel and distributed simulation. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/1853/61788.

Council of Science Editors:

Biswas A. Energy efficient parallel and distributed simulation. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61788

6. Lee, Joo Hwan. Relaxing coherence for modern learning applications.

Degree: PhD, Computer Science, 2017, Georgia Tech

 The main objective of this research is to efficiently execute learning (model training) of modern machine learning (ML) applications. The recent explosion in data has… (more)

Subjects/Keywords: Relaxing coherence; Stale value tolerance; Machine learning acceleration; Parallel learning; Computer architecture

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APA (6th Edition):

Lee, J. H. (2017). Relaxing coherence for modern learning applications. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58203

Chicago Manual of Style (16th Edition):

Lee, Joo Hwan. “Relaxing coherence for modern learning applications.” 2017. Doctoral Dissertation, Georgia Tech. Accessed October 17, 2019. http://hdl.handle.net/1853/58203.

MLA Handbook (7th Edition):

Lee, Joo Hwan. “Relaxing coherence for modern learning applications.” 2017. Web. 17 Oct 2019.

Vancouver:

Lee JH. Relaxing coherence for modern learning applications. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/1853/58203.

Council of Science Editors:

Lee JH. Relaxing coherence for modern learning applications. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/58203

7. Kang, Jane. Migration of blood cells in non-uniform suspension for a dialyzer design.

Degree: PhD, Mechanical Engineering, 2015, Georgia Tech

 Hemodialysis is a renal replacement therapy that removes waste solutes from the blood stream using concentration gradients across a membrane. In order to overcome several… (more)

Subjects/Keywords: Blood cell; Migration; Suspension; Nonuniform; Dialyzer; Hemodialysis

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APA (6th Edition):

Kang, J. (2015). Migration of blood cells in non-uniform suspension for a dialyzer design. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53871

Chicago Manual of Style (16th Edition):

Kang, Jane. “Migration of blood cells in non-uniform suspension for a dialyzer design.” 2015. Doctoral Dissertation, Georgia Tech. Accessed October 17, 2019. http://hdl.handle.net/1853/53871.

MLA Handbook (7th Edition):

Kang, Jane. “Migration of blood cells in non-uniform suspension for a dialyzer design.” 2015. Web. 17 Oct 2019.

Vancouver:

Kang J. Migration of blood cells in non-uniform suspension for a dialyzer design. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/1853/53871.

Council of Science Editors:

Kang J. Migration of blood cells in non-uniform suspension for a dialyzer design. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/53871

8. Choi, Jee Whan. Power and performance modeling for high-performance computing algorithms.

Degree: PhD, Electrical and Computer Engineering, 2015, Georgia Tech

 The overarching goal of this thesis is to provide an algorithm-centric approach to analyzing the relationship between time, energy, and power. This research is aimed… (more)

Subjects/Keywords: High-performance computing; Energy; Power; Performance; Modeling

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APA (6th Edition):

Choi, J. W. (2015). Power and performance modeling for high-performance computing algorithms. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53561

Chicago Manual of Style (16th Edition):

Choi, Jee Whan. “Power and performance modeling for high-performance computing algorithms.” 2015. Doctoral Dissertation, Georgia Tech. Accessed October 17, 2019. http://hdl.handle.net/1853/53561.

MLA Handbook (7th Edition):

Choi, Jee Whan. “Power and performance modeling for high-performance computing algorithms.” 2015. Web. 17 Oct 2019.

Vancouver:

Choi JW. Power and performance modeling for high-performance computing algorithms. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/1853/53561.

Council of Science Editors:

Choi JW. Power and performance modeling for high-performance computing algorithms. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/53561

9. Bangalore Lakshminarayana, Nagesh. Efficient graph algorithm execution on data-parallel architectures.

Degree: PhD, Computer Science, 2014, Georgia Tech

 Mechanisms for improving the execution efficiency of graph algorithms on Data-Parallel Architectures were proposed and identified. Execution of graph algorithms on GPGPU architectures, the prevalent… (more)

Subjects/Keywords: Graph algorithms; Data-parallel architectures; GPGPU architectures; Prefetching; Cache hierarchy; Inclusion property; Cache bypass; Fine-grained accesses; BFS characterization

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APA (6th Edition):

Bangalore Lakshminarayana, N. (2014). Efficient graph algorithm execution on data-parallel architectures. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53058

Chicago Manual of Style (16th Edition):

Bangalore Lakshminarayana, Nagesh. “Efficient graph algorithm execution on data-parallel architectures.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 17, 2019. http://hdl.handle.net/1853/53058.

MLA Handbook (7th Edition):

Bangalore Lakshminarayana, Nagesh. “Efficient graph algorithm execution on data-parallel architectures.” 2014. Web. 17 Oct 2019.

Vancouver:

Bangalore Lakshminarayana N. Efficient graph algorithm execution on data-parallel architectures. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/1853/53058.

Council of Science Editors:

Bangalore Lakshminarayana N. Efficient graph algorithm execution on data-parallel architectures. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/53058

10. Lee, Jaekyu. Shared resource management for efficient heterogeneous computing.

Degree: PhD, Computer Science, 2013, Georgia Tech

 The demand for heterogeneous computing, because of its performance and energy efficiency, has made on-chip heterogeneous chip multi-processors (HCMP) become the mainstream computing platform, as… (more)

Subjects/Keywords: Resource management; Heterogeneous architecture; Shared cache; On-chip network; Graphics processing units; Heterogeneous computing; Cache memory

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APA (6th Edition):

Lee, J. (2013). Shared resource management for efficient heterogeneous computing. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/50217

Chicago Manual of Style (16th Edition):

Lee, Jaekyu. “Shared resource management for efficient heterogeneous computing.” 2013. Doctoral Dissertation, Georgia Tech. Accessed October 17, 2019. http://hdl.handle.net/1853/50217.

MLA Handbook (7th Edition):

Lee, Jaekyu. “Shared resource management for efficient heterogeneous computing.” 2013. Web. 17 Oct 2019.

Vancouver:

Lee J. Shared resource management for efficient heterogeneous computing. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/1853/50217.

Council of Science Editors:

Lee J. Shared resource management for efficient heterogeneous computing. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/50217

11. Curtin, Ryan Ross. Improving dual-tree algorithms.

Degree: PhD, Electrical and Computer Engineering, 2015, Georgia Tech

 This large body of work is entirely centered around dual-tree algorithms, a class of algorithm based on spatial indexing structures that often provide large amounts… (more)

Subjects/Keywords: Machine learning; Computational geometry; Tree-based algorithms; Dual-tree algorithms; Kd-tree; Nearest neighbor search; K-means clustering; Data mining

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APA (6th Edition):

Curtin, R. R. (2015). Improving dual-tree algorithms. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54354

Chicago Manual of Style (16th Edition):

Curtin, Ryan Ross. “Improving dual-tree algorithms.” 2015. Doctoral Dissertation, Georgia Tech. Accessed October 17, 2019. http://hdl.handle.net/1853/54354.

MLA Handbook (7th Edition):

Curtin, Ryan Ross. “Improving dual-tree algorithms.” 2015. Web. 17 Oct 2019.

Vancouver:

Curtin RR. Improving dual-tree algorithms. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Oct 17]. Available from: http://hdl.handle.net/1853/54354.

Council of Science Editors:

Curtin RR. Improving dual-tree algorithms. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54354

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