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You searched for +publisher:"Virginia Tech" +contributor:("Cameron, Kirk W."). Showing records 1 – 27 of 27 total matches.

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Virginia Tech

1. Shirole, Sushrut Madhukar. Performance Optimizations for Isolated Driver Domains.

Degree: MS, Computer Science, 2014, Virginia Tech

 In most of today's operating system architectures, device drivers are tightly coupled with other kernel components. In such systems, a fault caused by a malicious… (more)

Subjects/Keywords: Virtualization; Device drivers

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APA (6th Edition):

Shirole, S. M. (2014). Performance Optimizations for Isolated Driver Domains. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/49107

Chicago Manual of Style (16th Edition):

Shirole, Sushrut Madhukar. “Performance Optimizations for Isolated Driver Domains.” 2014. Masters Thesis, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/49107.

MLA Handbook (7th Edition):

Shirole, Sushrut Madhukar. “Performance Optimizations for Isolated Driver Domains.” 2014. Web. 22 Sep 2019.

Vancouver:

Shirole SM. Performance Optimizations for Isolated Driver Domains. [Internet] [Masters thesis]. Virginia Tech; 2014. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/49107.

Council of Science Editors:

Shirole SM. Performance Optimizations for Isolated Driver Domains. [Masters Thesis]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/49107


Virginia Tech

2. 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 September 22, 2019. http://hdl.handle.net/10919/30260.

MLA Handbook (7th Edition):

Belgin, Mehmet. “Structure-based Optimizations for Sparse Matrix-Vector Multiply.” 2010. Web. 22 Sep 2019.

Vancouver:

Belgin M. Structure-based Optimizations for Sparse Matrix-Vector Multiply. [Internet] [Doctoral dissertation]. Virginia Tech; 2010. [cited 2019 Sep 22]. 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

3. 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 September 22, 2019. http://hdl.handle.net/10919/78677.

MLA Handbook (7th Edition):

Cheng, Yue. “Workload-aware Efficient Storage Systems.” 2017. Web. 22 Sep 2019.

Vancouver:

Cheng Y. Workload-aware Efficient Storage Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2017. [cited 2019 Sep 22]. 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

4. 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 September 22, 2019. http://hdl.handle.net/10919/47804.

MLA Handbook (7th Edition):

Li, Min. “A resource management framework for cloud computing.” 2014. Web. 22 Sep 2019.

Vancouver:

Li M. A resource management framework for cloud computing. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2019 Sep 22]. 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

5. Li, Dong. Scalable and Energy Efficient Execution Methods for Multicore Systems.

Degree: PhD, Computer Science, 2011, Virginia Tech

 Multicore architectures impose great pressure on resource management. The exploration spaces available for resource management increase explosively, especially for large-scale high end computing systems. The… (more)

Subjects/Keywords: Performance Modeling and Analysis; Multicore Processors; Power-Aware Computing; Concurrency Throttling; High-Performance Computing

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APA (6th Edition):

Li, D. (2011). Scalable and Energy Efficient Execution Methods for Multicore Systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/26098

Chicago Manual of Style (16th Edition):

Li, Dong. “Scalable and Energy Efficient Execution Methods for Multicore Systems.” 2011. Doctoral Dissertation, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/26098.

MLA Handbook (7th Edition):

Li, Dong. “Scalable and Energy Efficient Execution Methods for Multicore Systems.” 2011. Web. 22 Sep 2019.

Vancouver:

Li D. Scalable and Energy Efficient Execution Methods for Multicore Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/26098.

Council of Science Editors:

Li D. Scalable and Energy Efficient Execution Methods for Multicore Systems. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/26098


Virginia Tech

6. Li, Bo. Modeling and Runtime Systems for Coordinated Power-Performance Management.

Degree: PhD, Computer Science, 2019, Virginia Tech

 Emergent systems in high-performance computing (HPC) expect maximal efficiency to achieve the goal of power budget under 20-40 megawatts for 1 exaflop set by the… (more)

Subjects/Keywords: Parallel Performance Modeling; Dynamic Voltage and Frequency Scaling; Dynamic Memory Throttling; Dynamic Concurrency Throttling; Shared-Memory Systems

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APA (6th Edition):

Li, B. (2019). Modeling and Runtime Systems for Coordinated Power-Performance Management. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/87064

Chicago Manual of Style (16th Edition):

Li, Bo. “Modeling and Runtime Systems for Coordinated Power-Performance Management.” 2019. Doctoral Dissertation, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/87064.

MLA Handbook (7th Edition):

Li, Bo. “Modeling and Runtime Systems for Coordinated Power-Performance Management.” 2019. Web. 22 Sep 2019.

Vancouver:

Li B. Modeling and Runtime Systems for Coordinated Power-Performance Management. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/87064.

Council of Science Editors:

Li B. Modeling and Runtime Systems for Coordinated Power-Performance Management. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/87064


Virginia Tech

7. 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 September 22, 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. 22 Sep 2019.

Vancouver:

Xu L. A Workload-aware Resource Management and Scheduling System for Big Data Analysis. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2019 Sep 22]. 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

8. 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 September 22, 2019. http://hdl.handle.net/10919/30240.

MLA Handbook (7th Edition):

Schneider, Scott. “Shared Memory Abstractions for Heterogeneous Multicore Processors.” 2010. Web. 22 Sep 2019.

Vancouver:

Schneider S. Shared Memory Abstractions for Heterogeneous Multicore Processors. [Internet] [Doctoral dissertation]. Virginia Tech; 2010. [cited 2019 Sep 22]. 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


Virginia Tech

9. Wang, Guanying. Evaluating MapReduce System Performance: A Simulation Approach.

Degree: PhD, Computer Science, 2012, Virginia Tech

 Scale of data generated and processed is exploding in the Big Data era. The MapReduce system popularized by open-source Hadoop is a powerful tool for… (more)

Subjects/Keywords: performance prediction; performance modeling; simulation; MapReduce; Hadoop

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APA (6th Edition):

Wang, G. (2012). Evaluating MapReduce System Performance: A Simulation Approach. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28820

Chicago Manual of Style (16th Edition):

Wang, Guanying. “Evaluating MapReduce System Performance: A Simulation Approach.” 2012. Doctoral Dissertation, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/28820.

MLA Handbook (7th Edition):

Wang, Guanying. “Evaluating MapReduce System Performance: A Simulation Approach.” 2012. Web. 22 Sep 2019.

Vancouver:

Wang G. Evaluating MapReduce System Performance: A Simulation Approach. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/28820.

Council of Science Editors:

Wang G. Evaluating MapReduce System Performance: A Simulation Approach. [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/28820


Virginia Tech

10. Rafique, Muhammad Mustafa. An Adaptive Framework for Managing Heterogeneous Many-Core Clusters.

Degree: PhD, Computer Science, 2011, Virginia Tech

 The computing needs and the input and result datasets of modern scientific and enterprise applications are growing exponentially. To support such applications, High-Performance Computing (HPC)… (more)

Subjects/Keywords: Heterogeneous Computing; High-Performance Computing; Resource Sharing; Resource Management and Scheduling; Programming Models

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APA (6th Edition):

Rafique, M. M. (2011). An Adaptive Framework for Managing Heterogeneous Many-Core Clusters. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/29119

Chicago Manual of Style (16th Edition):

Rafique, Muhammad Mustafa. “An Adaptive Framework for Managing Heterogeneous Many-Core Clusters.” 2011. Doctoral Dissertation, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/29119.

MLA Handbook (7th Edition):

Rafique, Muhammad Mustafa. “An Adaptive Framework for Managing Heterogeneous Many-Core Clusters.” 2011. Web. 22 Sep 2019.

Vancouver:

Rafique MM. An Adaptive Framework for Managing Heterogeneous Many-Core Clusters. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/29119.

Council of Science Editors:

Rafique MM. An Adaptive Framework for Managing Heterogeneous Many-Core Clusters. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/29119


Virginia Tech

11. Easterling, David Robert. Solution of Constrained Clustering Problems through Homotopy Tracking.

Degree: PhD, Computer Science, 2015, Virginia Tech

 Modern machine learning methods are dependent on active optimization research to improve the set of methods available for the efficient and effective extraction of information… (more)

Subjects/Keywords: Multiobjective optimization; stochastic optimization; deterministic op- timization; biomechanics; quadratic optimization; DIRECT; QNSTOP; KNITRO; SPAN; simulated annealing; homotopy; constrained clustering

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APA (6th Edition):

Easterling, D. R. (2015). Solution of Constrained Clustering Problems through Homotopy Tracking. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/51189

Chicago Manual of Style (16th Edition):

Easterling, David Robert. “Solution of Constrained Clustering Problems through Homotopy Tracking.” 2015. Doctoral Dissertation, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/51189.

MLA Handbook (7th Edition):

Easterling, David Robert. “Solution of Constrained Clustering Problems through Homotopy Tracking.” 2015. Web. 22 Sep 2019.

Vancouver:

Easterling DR. Solution of Constrained Clustering Problems through Homotopy Tracking. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/51189.

Council of Science Editors:

Easterling DR. Solution of Constrained Clustering Problems through Homotopy Tracking. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/51189


Virginia Tech

12. Su, Chun-Yi. Energy-aware Thread and Data Management in Heterogeneous Multi-Core, Multi-Memory Systems.

Degree: PhD, Computer Science, 2015, Virginia Tech

 By 2004, microprocessor design focused on multicore scaling"increasing the number of cores per die in each generation "as the primary strategy for improving performance. These… (more)

Subjects/Keywords: Thread Management; Multi-core Processors; Performance Modeling and Analysis; Power-Aware Computing; Heterogeneous Memory; Data Management

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APA (6th Edition):

Su, C. (2015). Energy-aware Thread and Data Management in Heterogeneous Multi-Core, Multi-Memory Systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/51255

Chicago Manual of Style (16th Edition):

Su, Chun-Yi. “Energy-aware Thread and Data Management in Heterogeneous Multi-Core, Multi-Memory Systems.” 2015. Doctoral Dissertation, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/51255.

MLA Handbook (7th Edition):

Su, Chun-Yi. “Energy-aware Thread and Data Management in Heterogeneous Multi-Core, Multi-Memory Systems.” 2015. Web. 22 Sep 2019.

Vancouver:

Su C. Energy-aware Thread and Data Management in Heterogeneous Multi-Core, Multi-Memory Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/51255.

Council of Science Editors:

Su C. Energy-aware Thread and Data Management in Heterogeneous Multi-Core, Multi-Memory Systems. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/51255


Virginia Tech

13. Khasymski, Aleksandr Sergeev. Accelerated Storage Systems.

Degree: PhD, Computer Science, 2015, Virginia Tech

 Today's large-scale, high-performance, data-intensive applications put a tremendous stress on data centers to store, index, and retrieve large amounts of data. Exemplified by technologies such… (more)

Subjects/Keywords: Key-Value Store; Flash; Software RAID; Accelerator-based Computing

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APA (6th Edition):

Khasymski, A. S. (2015). Accelerated Storage Systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/51612

Chicago Manual of Style (16th Edition):

Khasymski, Aleksandr Sergeev. “Accelerated Storage Systems.” 2015. Doctoral Dissertation, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/51612.

MLA Handbook (7th Edition):

Khasymski, Aleksandr Sergeev. “Accelerated Storage Systems.” 2015. Web. 22 Sep 2019.

Vancouver:

Khasymski AS. Accelerated Storage Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/51612.

Council of Science Editors:

Khasymski AS. Accelerated Storage Systems. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/51612


Virginia Tech

14. Chang, Hung-Ching. Measuring, modeling, and optimizing counterintuitive performance phenomena in power-scalable, parallel systems.

Degree: PhD, Computer Science, 2015, Virginia Tech

 The demands of exascale computing systems and applications have pushed for a rapid, continual design paradigm coupled with increasing design complexities from the interaction between… (more)

Subjects/Keywords: parallel and distributed processing; I/O performance; power; runtime systems

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APA (6th Edition):

Chang, H. (2015). Measuring, modeling, and optimizing counterintuitive performance phenomena in power-scalable, parallel systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/51682

Chicago Manual of Style (16th Edition):

Chang, Hung-Ching. “Measuring, modeling, and optimizing counterintuitive performance phenomena in power-scalable, parallel systems.” 2015. Doctoral Dissertation, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/51682.

MLA Handbook (7th Edition):

Chang, Hung-Ching. “Measuring, modeling, and optimizing counterintuitive performance phenomena in power-scalable, parallel systems.” 2015. Web. 22 Sep 2019.

Vancouver:

Chang H. Measuring, modeling, and optimizing counterintuitive performance phenomena in power-scalable, parallel systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/51682.

Council of Science Editors:

Chang H. Measuring, modeling, and optimizing counterintuitive performance phenomena in power-scalable, parallel systems. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/51682


Virginia Tech

15. Song, Shuaiwen. Power, Performance and Energy Models and Systems for Emergent Architectures.

Degree: PhD, Computer Science, 2013, Virginia Tech

 Massive parallelism combined with complex memory hierarchies and heterogeneity in high-performance computing (HPC) systems form a barrier to efficient application and architecture design. The performance… (more)

Subjects/Keywords: High performance computing; power-aware computing; performance/energy modeling and optimization; runtime system

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APA (6th Edition):

Song, S. (2013). Power, Performance and Energy Models and Systems for Emergent Architectures. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/19316

Chicago Manual of Style (16th Edition):

Song, Shuaiwen. “Power, Performance and Energy Models and Systems for Emergent Architectures.” 2013. Doctoral Dissertation, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/19316.

MLA Handbook (7th Edition):

Song, Shuaiwen. “Power, Performance and Energy Models and Systems for Emergent Architectures.” 2013. Web. 22 Sep 2019.

Vancouver:

Song S. Power, Performance and Energy Models and Systems for Emergent Architectures. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/19316.

Council of Science Editors:

Song S. Power, Performance and Energy Models and Systems for Emergent Architectures. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/19316


Virginia Tech

16. Pyla, Hari Krishna. Tempest: A Framework for High Performance Thermal-Aware Distributed Computing.

Degree: MS, Computer Science, 2007, Virginia Tech

 Compute clusters are consuming more power at higher densities than ever before. This results in increased thermal dissipation, the need for powerful cooling systems, and… (more)

Subjects/Keywords: parallel processing; thermal profiling

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APA (6th Edition):

Pyla, H. K. (2007). Tempest: A Framework for High Performance Thermal-Aware Distributed Computing. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/33198

Chicago Manual of Style (16th Edition):

Pyla, Hari Krishna. “Tempest: A Framework for High Performance Thermal-Aware Distributed Computing.” 2007. Masters Thesis, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/33198.

MLA Handbook (7th Edition):

Pyla, Hari Krishna. “Tempest: A Framework for High Performance Thermal-Aware Distributed Computing.” 2007. Web. 22 Sep 2019.

Vancouver:

Pyla HK. Tempest: A Framework for High Performance Thermal-Aware Distributed Computing. [Internet] [Masters thesis]. Virginia Tech; 2007. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/33198.

Council of Science Editors:

Pyla HK. Tempest: A Framework for High Performance Thermal-Aware Distributed Computing. [Masters Thesis]. Virginia Tech; 2007. Available from: http://hdl.handle.net/10919/33198


Virginia Tech

17. Deodhar, Abhijit Anant. COPS: A Framework for Consumer Oriented Proportional share Scheduling.

Degree: MS, Computer Science, 2007, Virginia Tech

 Scheduling forms an important aspect of operating systems because it has a direct impact on system performance. Most existing general-purpose schedulers use a priority-based scheme… (more)

Subjects/Keywords: resource management; VTRR; proportional share; scheduling

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APA (6th Edition):

Deodhar, A. A. (2007). COPS: A Framework for Consumer Oriented Proportional share Scheduling. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/33232

Chicago Manual of Style (16th Edition):

Deodhar, Abhijit Anant. “COPS: A Framework for Consumer Oriented Proportional share Scheduling.” 2007. Masters Thesis, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/33232.

MLA Handbook (7th Edition):

Deodhar, Abhijit Anant. “COPS: A Framework for Consumer Oriented Proportional share Scheduling.” 2007. Web. 22 Sep 2019.

Vancouver:

Deodhar AA. COPS: A Framework for Consumer Oriented Proportional share Scheduling. [Internet] [Masters thesis]. Virginia Tech; 2007. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/33232.

Council of Science Editors:

Deodhar AA. COPS: A Framework for Consumer Oriented Proportional share Scheduling. [Masters Thesis]. Virginia Tech; 2007. Available from: http://hdl.handle.net/10919/33232


Virginia Tech

18. Aji, Ashwin Mandayam. Exploiting Multigrain Parallelism in Pairwise Sequence Search on Emergent CMP Architectures.

Degree: MS, Computer Science, 2008, Virginia Tech

 With the emerging hybrid multi-core and many-core compute platforms delivering unprecedented high performance within a single chip, and making rapid strides toward the commodity processor… (more)

Subjects/Keywords: GPGPU; Cell Broadband Engine; Smith-Waterman; Bioinformatics

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APA (6th Edition):

Aji, A. M. (2008). Exploiting Multigrain Parallelism in Pairwise Sequence Search on Emergent CMP Architectures. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/33606

Chicago Manual of Style (16th Edition):

Aji, Ashwin Mandayam. “Exploiting Multigrain Parallelism in Pairwise Sequence Search on Emergent CMP Architectures.” 2008. Masters Thesis, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/33606.

MLA Handbook (7th Edition):

Aji, Ashwin Mandayam. “Exploiting Multigrain Parallelism in Pairwise Sequence Search on Emergent CMP Architectures.” 2008. Web. 22 Sep 2019.

Vancouver:

Aji AM. Exploiting Multigrain Parallelism in Pairwise Sequence Search on Emergent CMP Architectures. [Internet] [Masters thesis]. Virginia Tech; 2008. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/33606.

Council of Science Editors:

Aji AM. Exploiting Multigrain Parallelism in Pairwise Sequence Search on Emergent CMP Architectures. [Masters Thesis]. Virginia Tech; 2008. Available from: http://hdl.handle.net/10919/33606


Virginia Tech

19. Cao, Zhenwei. Power Saving Analysis and Experiments for Large Scale Global Optimization.

Degree: MS, Computer Science, 2009, Virginia Tech

 Green computing, an emerging field of research that seeks to reduce excess power consumption in high performance computing (HPC), is gaining popularity among researchers. Research… (more)

Subjects/Keywords: VTDIRECT95; power aware computing; high performance computing; DVFS; large scale global optimization; budding yeast problem

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APA (6th Edition):

Cao, Z. (2009). Power Saving Analysis and Experiments for Large Scale Global Optimization. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/33944

Chicago Manual of Style (16th Edition):

Cao, Zhenwei. “Power Saving Analysis and Experiments for Large Scale Global Optimization.” 2009. Masters Thesis, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/33944.

MLA Handbook (7th Edition):

Cao, Zhenwei. “Power Saving Analysis and Experiments for Large Scale Global Optimization.” 2009. Web. 22 Sep 2019.

Vancouver:

Cao Z. Power Saving Analysis and Experiments for Large Scale Global Optimization. [Internet] [Masters thesis]. Virginia Tech; 2009. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/33944.

Council of Science Editors:

Cao Z. Power Saving Analysis and Experiments for Large Scale Global Optimization. [Masters Thesis]. Virginia Tech; 2009. Available from: http://hdl.handle.net/10919/33944


Virginia Tech

20. Basavaraj, Veena. Optimality of Heuristic Schedulers in Utility Accrual Real-time Scheduling Environments.

Degree: MS, Computer Science, 2006, Virginia Tech

 Scheduling decisions in soft real-time environments are based on a utility function. The goal of such schedulers is to use a best-effort approach to maximize… (more)

Subjects/Keywords: real-time; utility accrual; time-utility functions; optimality

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APA (6th Edition):

Basavaraj, V. (2006). Optimality of Heuristic Schedulers in Utility Accrual Real-time Scheduling Environments. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/33953

Chicago Manual of Style (16th Edition):

Basavaraj, Veena. “Optimality of Heuristic Schedulers in Utility Accrual Real-time Scheduling Environments.” 2006. Masters Thesis, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/33953.

MLA Handbook (7th Edition):

Basavaraj, Veena. “Optimality of Heuristic Schedulers in Utility Accrual Real-time Scheduling Environments.” 2006. Web. 22 Sep 2019.

Vancouver:

Basavaraj V. Optimality of Heuristic Schedulers in Utility Accrual Real-time Scheduling Environments. [Internet] [Masters thesis]. Virginia Tech; 2006. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/33953.

Council of Science Editors:

Basavaraj V. Optimality of Heuristic Schedulers in Utility Accrual Real-time Scheduling Environments. [Masters Thesis]. Virginia Tech; 2006. Available from: http://hdl.handle.net/10919/33953


Virginia Tech

21. Muthukumaraswamy Sivakumar, Vijay. An Evaluation of the Linux Virtual Memory Manager to Determine Suitability for Runtime Variation of Memory.

Degree: MS, Computer Science, 2007, Virginia Tech

 Systems that support virtual memory virtualize the available physical memory such that the applications running on them operate under the assumption that these systems have… (more)

Subjects/Keywords: virtual memory management; runtime variation of memory; application performance

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APA (6th Edition):

Muthukumaraswamy Sivakumar, V. (2007). An Evaluation of the Linux Virtual Memory Manager to Determine Suitability for Runtime Variation of Memory. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/31608

Chicago Manual of Style (16th Edition):

Muthukumaraswamy Sivakumar, Vijay. “An Evaluation of the Linux Virtual Memory Manager to Determine Suitability for Runtime Variation of Memory.” 2007. Masters Thesis, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/31608.

MLA Handbook (7th Edition):

Muthukumaraswamy Sivakumar, Vijay. “An Evaluation of the Linux Virtual Memory Manager to Determine Suitability for Runtime Variation of Memory.” 2007. Web. 22 Sep 2019.

Vancouver:

Muthukumaraswamy Sivakumar V. An Evaluation of the Linux Virtual Memory Manager to Determine Suitability for Runtime Variation of Memory. [Internet] [Masters thesis]. Virginia Tech; 2007. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/31608.

Council of Science Editors:

Muthukumaraswamy Sivakumar V. An Evaluation of the Linux Virtual Memory Manager to Determine Suitability for Runtime Variation of Memory. [Masters Thesis]. Virginia Tech; 2007. Available from: http://hdl.handle.net/10919/31608


Virginia Tech

22. Shah, Ankur Savailal. Prediction Models for Multi-dimensional Power-Performance Optimization on Many Cores.

Degree: MS, Computer Science, 2008, Virginia Tech

 Power has become a primary concern for HPC systems. Dynamic voltage and frequency scaling (DVFS) and dynamic concurrency throttling (DCT) are two software tools (or… (more)

Subjects/Keywords: concurrency throttling; power-aware computing; runtime adaptation; performance prediction; high-performance computing; Multicore processors

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APA (6th Edition):

Shah, A. S. (2008). Prediction Models for Multi-dimensional Power-Performance Optimization on Many Cores. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/31826

Chicago Manual of Style (16th Edition):

Shah, Ankur Savailal. “Prediction Models for Multi-dimensional Power-Performance Optimization on Many Cores.” 2008. Masters Thesis, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/31826.

MLA Handbook (7th Edition):

Shah, Ankur Savailal. “Prediction Models for Multi-dimensional Power-Performance Optimization on Many Cores.” 2008. Web. 22 Sep 2019.

Vancouver:

Shah AS. Prediction Models for Multi-dimensional Power-Performance Optimization on Many Cores. [Internet] [Masters thesis]. Virginia Tech; 2008. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/31826.

Council of Science Editors:

Shah AS. Prediction Models for Multi-dimensional Power-Performance Optimization on Many Cores. [Masters Thesis]. Virginia Tech; 2008. Available from: http://hdl.handle.net/10919/31826


Virginia Tech

23. Blagojevic, Filip. Scheduling on Asymmetric Architectures.

Degree: PhD, Computer Science, 2008, Virginia Tech

 We explore runtime mechanisms and policies for scheduling dynamic multi-grain parallelism on heterogeneous multi-core processors. Heterogeneous multi-core processors integrate conventional cores that run legacy codes… (more)

Subjects/Keywords: process scheduling; performance prediction; high-performance computing; runtime adaptation; Multicore processors; Cell BE

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APA (6th Edition):

Blagojevic, F. (2008). Scheduling on Asymmetric Architectures. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/27952

Chicago Manual of Style (16th Edition):

Blagojevic, Filip. “Scheduling on Asymmetric Architectures.” 2008. Doctoral Dissertation, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/27952.

MLA Handbook (7th Edition):

Blagojevic, Filip. “Scheduling on Asymmetric Architectures.” 2008. Web. 22 Sep 2019.

Vancouver:

Blagojevic F. Scheduling on Asymmetric Architectures. [Internet] [Doctoral dissertation]. Virginia Tech; 2008. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/27952.

Council of Science Editors:

Blagojevic F. Scheduling on Asymmetric Architectures. [Doctoral Dissertation]. Virginia Tech; 2008. Available from: http://hdl.handle.net/10919/27952


Virginia Tech

24. Ge, Rong. Theories and Techniques for Efficient High-End Computing.

Degree: PhD, Computer Science, 2007, Virginia Tech

 Today, power consumption costs supercomputer centers millions of dollars annually and the heat produced can reduce system reliability and availability. Achieving high performance while reducing… (more)

Subjects/Keywords: High-performance computing; power and performance management; power-performance efficiency; performance modeling and analysis

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APA (6th Edition):

Ge, R. (2007). Theories and Techniques for Efficient High-End Computing. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28863

Chicago Manual of Style (16th Edition):

Ge, Rong. “Theories and Techniques for Efficient High-End Computing.” 2007. Doctoral Dissertation, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/28863.

MLA Handbook (7th Edition):

Ge, Rong. “Theories and Techniques for Efficient High-End Computing.” 2007. Web. 22 Sep 2019.

Vancouver:

Ge R. Theories and Techniques for Efficient High-End Computing. [Internet] [Doctoral dissertation]. Virginia Tech; 2007. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/28863.

Council of Science Editors:

Ge R. Theories and Techniques for Efficient High-End Computing. [Doctoral Dissertation]. Virginia Tech; 2007. Available from: http://hdl.handle.net/10919/28863


Virginia Tech

25. Sudarsan, Rajesh. ReSHAPE: A Framework for Dynamic Resizing of Parallel Applications.

Degree: PhD, Computer Science, 2009, Virginia Tech

 As terascale supercomputers become more common, and as the high-performance computing community turns its attention to petascale machines, the challenge of providing effective resource management… (more)

Subjects/Keywords: Resizing LAMMPS; ReSHAPE; priority scheduling; adaptive resizing; data redistribution

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APA (6th Edition):

Sudarsan, R. (2009). ReSHAPE: A Framework for Dynamic Resizing of Parallel Applications. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/29137

Chicago Manual of Style (16th Edition):

Sudarsan, Rajesh. “ReSHAPE: A Framework for Dynamic Resizing of Parallel Applications.” 2009. Doctoral Dissertation, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/29137.

MLA Handbook (7th Edition):

Sudarsan, Rajesh. “ReSHAPE: A Framework for Dynamic Resizing of Parallel Applications.” 2009. Web. 22 Sep 2019.

Vancouver:

Sudarsan R. ReSHAPE: A Framework for Dynamic Resizing of Parallel Applications. [Internet] [Doctoral dissertation]. Virginia Tech; 2009. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/29137.

Council of Science Editors:

Sudarsan R. ReSHAPE: A Framework for Dynamic Resizing of Parallel Applications. [Doctoral Dissertation]. Virginia Tech; 2009. Available from: http://hdl.handle.net/10919/29137


Virginia Tech

26. Curtis-Maury, Matthew. Improving the Efficiency of Parallel Applications on Multithreaded and Multicore Systems.

Degree: PhD, Computer Science, 2008, Virginia Tech

 The scalability of parallel applications executing on multithreaded and multicore multiprocessors is often quite limited due to large degrees of contention over shared resources on… (more)

Subjects/Keywords: power-aware computing; high-performance computing; performance prediction; multicore processors; runtime adaptation; concurrency throttling

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APA (6th Edition):

Curtis-Maury, M. (2008). Improving the Efficiency of Parallel Applications on Multithreaded and Multicore Systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/26697

Chicago Manual of Style (16th Edition):

Curtis-Maury, Matthew. “Improving the Efficiency of Parallel Applications on Multithreaded and Multicore Systems.” 2008. Doctoral Dissertation, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/26697.

MLA Handbook (7th Edition):

Curtis-Maury, Matthew. “Improving the Efficiency of Parallel Applications on Multithreaded and Multicore Systems.” 2008. Web. 22 Sep 2019.

Vancouver:

Curtis-Maury M. Improving the Efficiency of Parallel Applications on Multithreaded and Multicore Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2008. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/26697.

Council of Science Editors:

Curtis-Maury M. Improving the Efficiency of Parallel Applications on Multithreaded and Multicore Systems. [Doctoral Dissertation]. Virginia Tech; 2008. Available from: http://hdl.handle.net/10919/26697


Virginia Tech

27. Tolentino, Matthew Edward. Managing Memory for Power, Performance, and Thermal Efficiency.

Degree: PhD, Computer Science, 2009, Virginia Tech

 Extraordinary improvements in computing performance, density, and capacity have driven rapid increases in system energy consumption, motivating the need for energy-efficient performance. Harnessing the collective… (more)

Subjects/Keywords: Energy Efficiency; Control Theory; Memory Management; Operating Systems

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APA (6th Edition):

Tolentino, M. E. (2009). Managing Memory for Power, Performance, and Thermal Efficiency. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/26301

Chicago Manual of Style (16th Edition):

Tolentino, Matthew Edward. “Managing Memory for Power, Performance, and Thermal Efficiency.” 2009. Doctoral Dissertation, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/26301.

MLA Handbook (7th Edition):

Tolentino, Matthew Edward. “Managing Memory for Power, Performance, and Thermal Efficiency.” 2009. Web. 22 Sep 2019.

Vancouver:

Tolentino ME. Managing Memory for Power, Performance, and Thermal Efficiency. [Internet] [Doctoral dissertation]. Virginia Tech; 2009. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/26301.

Council of Science Editors:

Tolentino ME. Managing Memory for Power, Performance, and Thermal Efficiency. [Doctoral Dissertation]. Virginia Tech; 2009. Available from: http://hdl.handle.net/10919/26301

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