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You searched for +publisher:"University of Texas – Austin" +contributor:("Pingali, Keshav"). Showing records 1 – 30 of 41 total matches.

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1. Dhanapal, Manoj. Design and implementation of distributed Galois.

Degree: MSin Computer Sciences, Computer Science, 2013, University of Texas – Austin

 The Galois system provides a solution to the hard problem of parallelizing irregular algorithms using amorphous data-parallelism. The present system works on the shared-memory programming… (more)

Subjects/Keywords: Galois; Parallel computing; Distributed computing

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APA (6th Edition):

Dhanapal, M. (2013). Design and implementation of distributed Galois. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/21643

Chicago Manual of Style (16th Edition):

Dhanapal, Manoj. “Design and implementation of distributed Galois.” 2013. Masters Thesis, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/21643.

MLA Handbook (7th Edition):

Dhanapal, Manoj. “Design and implementation of distributed Galois.” 2013. Web. 24 Jan 2021.

Vancouver:

Dhanapal M. Design and implementation of distributed Galois. [Internet] [Masters thesis]. University of Texas – Austin; 2013. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/21643.

Council of Science Editors:

Dhanapal M. Design and implementation of distributed Galois. [Masters Thesis]. University of Texas – Austin; 2013. Available from: http://hdl.handle.net/2152/21643


University of Texas – Austin

2. Xie, Chao, Ph. D. High-performance transactional storage.

Degree: PhD, Computer science, 2016, University of Texas – Austin

 Developers face a fundamental tension between performance and ease of programming when building complex applications. On the one hand, by freeing developers from having to… (more)

Subjects/Keywords: Transaction; High-performance; Distributed database

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APA (6th Edition):

Xie, Chao, P. D. (2016). High-performance transactional storage. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/42014

Chicago Manual of Style (16th Edition):

Xie, Chao, Ph D. “High-performance transactional storage.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/42014.

MLA Handbook (7th Edition):

Xie, Chao, Ph D. “High-performance transactional storage.” 2016. Web. 24 Jan 2021.

Vancouver:

Xie, Chao PD. High-performance transactional storage. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/42014.

Council of Science Editors:

Xie, Chao PD. High-performance transactional storage. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/42014

3. Celik, Ahmet. Proof engineering for large-scale verification projects.

Degree: PhD, Computer Science, 2019, University of Texas – Austin

 Software controls many aspects of our daily lives, thus, software correctness is of utmost importance. One way to develop correct-by-construction software is by using proof… (more)

Subjects/Keywords: Proof assistants; Verification; Parallelism; Proof engineering; Proof selection; Regression testing; Mutation testing; Coq

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APA (6th Edition):

Celik, A. (2019). Proof engineering for large-scale verification projects. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/5348

Chicago Manual of Style (16th Edition):

Celik, Ahmet. “Proof engineering for large-scale verification projects.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://dx.doi.org/10.26153/tsw/5348.

MLA Handbook (7th Edition):

Celik, Ahmet. “Proof engineering for large-scale verification projects.” 2019. Web. 24 Jan 2021.

Vancouver:

Celik A. Proof engineering for large-scale verification projects. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2021 Jan 24]. Available from: http://dx.doi.org/10.26153/tsw/5348.

Council of Science Editors:

Celik A. Proof engineering for large-scale verification projects. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/5348

4. Yaghmazadeh, Navid. Automated synthesis of data extraction and transformation programs.

Degree: PhD, Computer Science, 2017, University of Texas – Austin

 Due to the abundance of data in today’s data-rich world, end-users increasingly need to perform various data extraction and transformation tasks. While many of these… (more)

Subjects/Keywords: Program synthesis; Programming-by-examples; Programming-by-natural-language; Databases

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APA (6th Edition):

Yaghmazadeh, N. (2017). Automated synthesis of data extraction and transformation programs. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68138

Chicago Manual of Style (16th Edition):

Yaghmazadeh, Navid. “Automated synthesis of data extraction and transformation programs.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/68138.

MLA Handbook (7th Edition):

Yaghmazadeh, Navid. “Automated synthesis of data extraction and transformation programs.” 2017. Web. 24 Jan 2021.

Vancouver:

Yaghmazadeh N. Automated synthesis of data extraction and transformation programs. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/68138.

Council of Science Editors:

Yaghmazadeh N. Automated synthesis of data extraction and transformation programs. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/68138


University of Texas – Austin

5. Dathathri, Roshan. Compiler and runtime systems for homomorphic encryption and graph processing on distributed and heterogeneous architectures.

Degree: PhD, Computer Science, 2020, University of Texas – Austin

 Distributed and heterogeneous architectures are tedious to program because devices such as CPUs, GPUs, and FPGAs provide different programming abstractions and may have disjoint memories,… (more)

Subjects/Keywords: Compiler; Runtime system; Big data; Graph analytics; Distributed-memory; Heterogeneous architectures; GPUs; Communication optimizations; Homomorphic encryption; Neural networks; Privacy-preserving machine learning

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APA (6th Edition):

Dathathri, R. (2020). Compiler and runtime systems for homomorphic encryption and graph processing on distributed and heterogeneous architectures. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/10165

Chicago Manual of Style (16th Edition):

Dathathri, Roshan. “Compiler and runtime systems for homomorphic encryption and graph processing on distributed and heterogeneous architectures.” 2020. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://dx.doi.org/10.26153/tsw/10165.

MLA Handbook (7th Edition):

Dathathri, Roshan. “Compiler and runtime systems for homomorphic encryption and graph processing on distributed and heterogeneous architectures.” 2020. Web. 24 Jan 2021.

Vancouver:

Dathathri R. Compiler and runtime systems for homomorphic encryption and graph processing on distributed and heterogeneous architectures. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2020. [cited 2021 Jan 24]. Available from: http://dx.doi.org/10.26153/tsw/10165.

Council of Science Editors:

Dathathri R. Compiler and runtime systems for homomorphic encryption and graph processing on distributed and heterogeneous architectures. [Doctoral Dissertation]. University of Texas – Austin; 2020. Available from: http://dx.doi.org/10.26153/tsw/10165

6. -2502-2946. Theory and practice of classical matrix-matrix multiplication for hierarchical memory architectures.

Degree: PhD, Computer Science, 2018, University of Texas – Austin

 Matrix-matrix multiplication is perhaps the most important operation used as a basic building block in dense linear algebra. A computer with a hierarchical memory architectures… (more)

Subjects/Keywords: Linear algebra; Scientific computing; High-performance; Matrix; I/O complexity

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APA (6th Edition):

-2502-2946. (2018). Theory and practice of classical matrix-matrix multiplication for hierarchical memory architectures. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63352

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Author name may be incomplete

Chicago Manual of Style (16th Edition):

-2502-2946. “Theory and practice of classical matrix-matrix multiplication for hierarchical memory architectures.” 2018. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/63352.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-2502-2946. “Theory and practice of classical matrix-matrix multiplication for hierarchical memory architectures.” 2018. Web. 24 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-2502-2946. Theory and practice of classical matrix-matrix multiplication for hierarchical memory architectures. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2018. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/63352.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-2502-2946. Theory and practice of classical matrix-matrix multiplication for hierarchical memory architectures. [Doctoral Dissertation]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/63352

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Author name may be incomplete

7. Wang, Xinyu. An efficient programming-by-example framework.

Degree: PhD, Computer Science, 2019, University of Texas – Austin

 Due to the ubiquity of computing, programming has started to become an essential skill for an increasing number of people, including data scientists, financial analysts,… (more)

Subjects/Keywords: Programming languages; Program synthesis

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APA (6th Edition):

Wang, X. (2019). An efficient programming-by-example framework. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/5854

Chicago Manual of Style (16th Edition):

Wang, Xinyu. “An efficient programming-by-example framework.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://dx.doi.org/10.26153/tsw/5854.

MLA Handbook (7th Edition):

Wang, Xinyu. “An efficient programming-by-example framework.” 2019. Web. 24 Jan 2021.

Vancouver:

Wang X. An efficient programming-by-example framework. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2021 Jan 24]. Available from: http://dx.doi.org/10.26153/tsw/5854.

Council of Science Editors:

Wang X. An efficient programming-by-example framework. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/5854


University of Texas – Austin

8. Ma, Xiaoyu, Ph. D. Large-scale transactional execution of FPGA-accelerated irregular applications.

Degree: PhD, Electrical and Computer Engineering, 2017, University of Texas – Austin

 Irregular workloads are programs organized around pointer-based data structures such as graphs. They are widely used in many fields such as computer/human network analysis, machine… (more)

Subjects/Keywords: Transactional memory; Irregular application; Graph; FPGA; High-throughput compute

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APA (6th Edition):

Ma, Xiaoyu, P. D. (2017). Large-scale transactional execution of FPGA-accelerated irregular applications. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63014

Chicago Manual of Style (16th Edition):

Ma, Xiaoyu, Ph D. “Large-scale transactional execution of FPGA-accelerated irregular applications.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/63014.

MLA Handbook (7th Edition):

Ma, Xiaoyu, Ph D. “Large-scale transactional execution of FPGA-accelerated irregular applications.” 2017. Web. 24 Jan 2021.

Vancouver:

Ma, Xiaoyu PD. Large-scale transactional execution of FPGA-accelerated irregular applications. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/63014.

Council of Science Editors:

Ma, Xiaoyu PD. Large-scale transactional execution of FPGA-accelerated irregular applications. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/63014


University of Texas – Austin

9. Lavasani, Maysam. Generating irregular data-stream accelerators : methodology and applications.

Degree: PhD, Electrical and Computer Engineering, 2015, University of Texas – Austin

 This thesis presents Gorilla++, a language and a compiler for generating customized hardware accelerators that process input streams of data. Gorilla++ uses a hierarchical programming… (more)

Subjects/Keywords: Hardware accelerators; High-level synthesis; Auto-refinement; Big-data

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APA (6th Edition):

Lavasani, M. (2015). Generating irregular data-stream accelerators : methodology and applications. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/31409

Chicago Manual of Style (16th Edition):

Lavasani, Maysam. “Generating irregular data-stream accelerators : methodology and applications.” 2015. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/31409.

MLA Handbook (7th Edition):

Lavasani, Maysam. “Generating irregular data-stream accelerators : methodology and applications.” 2015. Web. 24 Jan 2021.

Vancouver:

Lavasani M. Generating irregular data-stream accelerators : methodology and applications. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2015. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/31409.

Council of Science Editors:

Lavasani M. Generating irregular data-stream accelerators : methodology and applications. [Doctoral Dissertation]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/31409

10. -3217-4051. Fine-grained containment domains for throughput processors.

Degree: PhD, Electrical and Computer Engineering, 2015, University of Texas – Austin

 Continued scaling of semiconductor technology has made modern processors rely on large design margins to guarantee correct operation under worst case conditions. Design margins appear… (more)

Subjects/Keywords: Resilience; Containment domains; Computer architecture; Timing speculation; GPU; Design margin; Voltage droop; Checkpoint-recovery

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APA (6th Edition):

-3217-4051. (2015). Fine-grained containment domains for throughput processors. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46990

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Author name may be incomplete

Chicago Manual of Style (16th Edition):

-3217-4051. “Fine-grained containment domains for throughput processors.” 2015. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/46990.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-3217-4051. “Fine-grained containment domains for throughput processors.” 2015. Web. 24 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-3217-4051. Fine-grained containment domains for throughput processors. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2015. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/46990.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-3217-4051. Fine-grained containment domains for throughput processors. [Doctoral Dissertation]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/46990

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


University of Texas – Austin

11. -8499-7554. Galois : a system for parallel execution of irregular algorithms.

Degree: PhD, Computer Sciences, 2015, University of Texas – Austin

 A programming model which allows users to program with high productivity and which produces high performance executions has been a goal for decades. This dissertation… (more)

Subjects/Keywords: Parallel programming; Multicore

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APA (6th Edition):

-8499-7554. (2015). Galois : a system for parallel execution of irregular algorithms. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/30536

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Author name may be incomplete

Chicago Manual of Style (16th Edition):

-8499-7554. “Galois : a system for parallel execution of irregular algorithms.” 2015. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/30536.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-8499-7554. “Galois : a system for parallel execution of irregular algorithms.” 2015. Web. 24 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-8499-7554. Galois : a system for parallel execution of irregular algorithms. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2015. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/30536.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-8499-7554. Galois : a system for parallel execution of irregular algorithms. [Doctoral Dissertation]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/30536

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


University of Texas – Austin

12. Nedunuri, Srinivas. Theory and techniques for synthesizing efficient breadth-first search algorithms.

Degree: PhD, Computer Science, 2012, University of Texas – Austin

 The development of efficient algorithms to solve a wide variety of combinatorial and planning problems is a significant achievement in computer science. Traditionally each algorithm… (more)

Subjects/Keywords: Program synthesis; Algorithms; Formal methods; AI; Search algorithms

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APA (6th Edition):

Nedunuri, S. (2012). Theory and techniques for synthesizing efficient breadth-first search algorithms. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-08-6242

Chicago Manual of Style (16th Edition):

Nedunuri, Srinivas. “Theory and techniques for synthesizing efficient breadth-first search algorithms.” 2012. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/ETD-UT-2012-08-6242.

MLA Handbook (7th Edition):

Nedunuri, Srinivas. “Theory and techniques for synthesizing efficient breadth-first search algorithms.” 2012. Web. 24 Jan 2021.

Vancouver:

Nedunuri S. Theory and techniques for synthesizing efficient breadth-first search algorithms. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2012. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-08-6242.

Council of Science Editors:

Nedunuri S. Theory and techniques for synthesizing efficient breadth-first search algorithms. [Doctoral Dissertation]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-08-6242


University of Texas – Austin

13. -9048-1017. Exploiting long-term behavior for improved memory system performance.

Degree: PhD, Computer science, 2016, University of Texas – Austin

 Memory latency is a key bottleneck for many programs. Caching and prefetching are two popular hardware mechanisms to alleviate the impact of long memory latencies,… (more)

Subjects/Keywords: Caches; Replacement policy; Prefetching; Memory system

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APA (6th Edition):

-9048-1017. (2016). Exploiting long-term behavior for improved memory system performance. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/42015

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Author name may be incomplete

Chicago Manual of Style (16th Edition):

-9048-1017. “Exploiting long-term behavior for improved memory system performance.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/42015.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-9048-1017. “Exploiting long-term behavior for improved memory system performance.” 2016. Web. 24 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-9048-1017. Exploiting long-term behavior for improved memory system performance. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/42015.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-9048-1017. Exploiting long-term behavior for improved memory system performance. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/42015

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


University of Texas – Austin

14. Lee, Dongwook. Learning-based system-level power modeling of hardware IPs.

Degree: PhD, Electrical and Computer Engineering, 2017, University of Texas – Austin

 Accurate power models for hardware components at high levels of abstraction are a critical component to enable system-level power analysis and optimization. Virtual platform prototypes… (more)

Subjects/Keywords: Power estimation; High-level synthesis

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APA (6th Edition):

Lee, D. (2017). Learning-based system-level power modeling of hardware IPs. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63013

Chicago Manual of Style (16th Edition):

Lee, Dongwook. “Learning-based system-level power modeling of hardware IPs.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/63013.

MLA Handbook (7th Edition):

Lee, Dongwook. “Learning-based system-level power modeling of hardware IPs.” 2017. Web. 24 Jan 2021.

Vancouver:

Lee D. Learning-based system-level power modeling of hardware IPs. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/63013.

Council of Science Editors:

Lee D. Learning-based system-level power modeling of hardware IPs. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/63013


University of Texas – Austin

15. Whang, Joyce Jiyoung. Overlapping community detection in massive social networks.

Degree: PhD, Computer science, 2015, University of Texas – Austin

 Massive social networks have become increasingly popular in recent years. Community detection is one of the most important techniques for the analysis of such complex… (more)

Subjects/Keywords: Community detection; Clustering; Social networks; Overlapping communities; Overlapping clusters; Non-exhaustive clustering; Seed expansion; K-means; Semidefinite programming; Co-clustering; PageRank; Data-driven algorithm; Scalable computing

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APA (6th Edition):

Whang, J. J. (2015). Overlapping community detection in massive social networks. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/33272

Chicago Manual of Style (16th Edition):

Whang, Joyce Jiyoung. “Overlapping community detection in massive social networks.” 2015. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/33272.

MLA Handbook (7th Edition):

Whang, Joyce Jiyoung. “Overlapping community detection in massive social networks.” 2015. Web. 24 Jan 2021.

Vancouver:

Whang JJ. Overlapping community detection in massive social networks. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2015. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/33272.

Council of Science Editors:

Whang JJ. Overlapping community detection in massive social networks. [Doctoral Dissertation]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/33272


University of Texas – Austin

16. Sui, Xin, Ph.D. Principled control of approximate programs.

Degree: PhD, Computer science, 2015, University of Texas – Austin

 In conventional computing, most programs are treated as implementations of mathematical functions for which there is an exact output that must computed from a given… (more)

Subjects/Keywords: Approximate computing; Error model; Cost model; Tunable approximate algorithms; Energy efficiency; Information efficiency; Systematic; Control; Tunable approximate programs

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APA (6th Edition):

Sui, Xin, P. D. (2015). Principled control of approximate programs. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/43722

Chicago Manual of Style (16th Edition):

Sui, Xin, Ph D. “Principled control of approximate programs.” 2015. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/43722.

MLA Handbook (7th Edition):

Sui, Xin, Ph D. “Principled control of approximate programs.” 2015. Web. 24 Jan 2021.

Vancouver:

Sui, Xin PD. Principled control of approximate programs. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2015. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/43722.

Council of Science Editors:

Sui, Xin PD. Principled control of approximate programs. [Doctoral Dissertation]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/43722


University of Texas – Austin

17. Mir arabbaygi, Siavash. Novel scalable approaches for multiple sequence alignment and phylogenomic reconstruction.

Degree: PhD, Computer science, 2015, University of Texas – Austin

 The amount of biological sequence data is increasing rapidly, a promising development that would transform biology if we can develop methods that can analyze large-scale… (more)

Subjects/Keywords: Phylogenetics; Multi-species coalescent model; Multiple sequence alignment; Statistical binning; Species tree estimation

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APA (6th Edition):

Mir arabbaygi, S. (2015). Novel scalable approaches for multiple sequence alignment and phylogenomic reconstruction. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/31377

Chicago Manual of Style (16th Edition):

Mir arabbaygi, Siavash. “Novel scalable approaches for multiple sequence alignment and phylogenomic reconstruction.” 2015. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/31377.

MLA Handbook (7th Edition):

Mir arabbaygi, Siavash. “Novel scalable approaches for multiple sequence alignment and phylogenomic reconstruction.” 2015. Web. 24 Jan 2021.

Vancouver:

Mir arabbaygi S. Novel scalable approaches for multiple sequence alignment and phylogenomic reconstruction. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2015. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/31377.

Council of Science Editors:

Mir arabbaygi S. Novel scalable approaches for multiple sequence alignment and phylogenomic reconstruction. [Doctoral Dissertation]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/31377


University of Texas – Austin

18. Gopinath, Divya. Systematic techniques for more effective fault localization and program repair.

Degree: PhD, Electrical and Computer engineering, 2015, University of Texas – Austin

 Debugging faulty code is a tedious process that is often quite expensive and can require much manual effort. Developers typically perform debugging in two key… (more)

Subjects/Keywords: Software debugging; Program repair; Fault localization; SAT; Correctness specifications; Classifier learning

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APA (6th Edition):

Gopinath, D. (2015). Systematic techniques for more effective fault localization and program repair. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/33386

Chicago Manual of Style (16th Edition):

Gopinath, Divya. “Systematic techniques for more effective fault localization and program repair.” 2015. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/33386.

MLA Handbook (7th Edition):

Gopinath, Divya. “Systematic techniques for more effective fault localization and program repair.” 2015. Web. 24 Jan 2021.

Vancouver:

Gopinath D. Systematic techniques for more effective fault localization and program repair. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2015. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/33386.

Council of Science Editors:

Gopinath D. Systematic techniques for more effective fault localization and program repair. [Doctoral Dissertation]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/33386


University of Texas – Austin

19. -5275-5590. Elixir: synthesis of parallel irregular algorithms.

Degree: PhD, Computer Science, 2015, University of Texas – Austin

 Algorithms in new application areas like machine learning and data analytics usually operate on unstructured sparse graphs. Writing efficient parallel code to implement these algorithms… (more)

Subjects/Keywords: Parallel programming; Programming languages; Compilers; Static analysis; Synthesis

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APA (6th Edition):

-5275-5590. (2015). Elixir: synthesis of parallel irregular algorithms. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/33278

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Author name may be incomplete

Chicago Manual of Style (16th Edition):

-5275-5590. “Elixir: synthesis of parallel irregular algorithms.” 2015. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/33278.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-5275-5590. “Elixir: synthesis of parallel irregular algorithms.” 2015. Web. 24 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-5275-5590. Elixir: synthesis of parallel irregular algorithms. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2015. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/33278.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-5275-5590. Elixir: synthesis of parallel irregular algorithms. [Doctoral Dissertation]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/33278

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


University of Texas – Austin

20. -1624-1733. Exploiting structure in large-scale optimization for machine learning.

Degree: PhD, Computer science, 2015, University of Texas – Austin

 With an immense growth of data, there is a great need for solving large-scale machine learning problems. Classical optimization algorithms usually cannot scale up due… (more)

Subjects/Keywords: Machine learning; Optimization

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APA (6th Edition):

-1624-1733. (2015). Exploiting structure in large-scale optimization for machine learning. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/31381

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Author name may be incomplete

Chicago Manual of Style (16th Edition):

-1624-1733. “Exploiting structure in large-scale optimization for machine learning.” 2015. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/31381.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-1624-1733. “Exploiting structure in large-scale optimization for machine learning.” 2015. Web. 24 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-1624-1733. Exploiting structure in large-scale optimization for machine learning. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2015. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/31381.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-1624-1733. Exploiting structure in large-scale optimization for machine learning. [Doctoral Dissertation]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/31381

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Author name may be incomplete


University of Texas – Austin

21. -7791-5469. Performance, power, and confidence modeling of digital designs.

Degree: PhD, Electrical and Computer engineering, 2015, University of Texas – Austin

 This dissertation presents three modeling methodologies. The first methodology constructs power models for system-on-chip (SoC) designs. The modeling approach uses a gate-level netlist description of… (more)

Subjects/Keywords: Power modeling; Confidence modeling; Machine learning

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APA (6th Edition):

-7791-5469. (2015). Performance, power, and confidence modeling of digital designs. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/31420

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Author name may be incomplete

Chicago Manual of Style (16th Edition):

-7791-5469. “Performance, power, and confidence modeling of digital designs.” 2015. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/31420.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-7791-5469. “Performance, power, and confidence modeling of digital designs.” 2015. Web. 24 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-7791-5469. Performance, power, and confidence modeling of digital designs. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2015. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/31420.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-7791-5469. Performance, power, and confidence modeling of digital designs. [Doctoral Dissertation]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/31420

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Author name may be incomplete


University of Texas – Austin

22. Yu, Hsiang-Fu. Scalable algorithms for latent variable models in machine learning.

Degree: PhD, Computer science, 2016, University of Texas – Austin

 Latent variable modeling (LVM) is a popular approach in many machine learning applications, such as recommender systems and topic modeling, due to its ability to… (more)

Subjects/Keywords: Latent variable modeling; Matrix factorization; Algorithms; Data

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APA (6th Edition):

Yu, H. (2016). Scalable algorithms for latent variable models in machine learning. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/41635

Chicago Manual of Style (16th Edition):

Yu, Hsiang-Fu. “Scalable algorithms for latent variable models in machine learning.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/41635.

MLA Handbook (7th Edition):

Yu, Hsiang-Fu. “Scalable algorithms for latent variable models in machine learning.” 2016. Web. 24 Jan 2021.

Vancouver:

Yu H. Scalable algorithms for latent variable models in machine learning. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/41635.

Council of Science Editors:

Yu H. Scalable algorithms for latent variable models in machine learning. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/41635


University of Texas – Austin

23. -5112-1839. Lightweight offload engines for worklist management and worklist-directed prefetching.

Degree: PhD, Electrical and Computer Engineering, 2018, University of Texas – Austin

 The importance of irregular applications such as graph analytics is rapidly growing with the rise of Big Data. However, parallel graph workloads tend to perform… (more)

Subjects/Keywords: Computer architecture; Graph algorithms; Parallel processors; Parallel programming; Prefetching; Accelerators; Scheduling; Task partitioning

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APA (6th Edition):

-5112-1839. (2018). Lightweight offload engines for worklist management and worklist-directed prefetching. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68554

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Author name may be incomplete

Chicago Manual of Style (16th Edition):

-5112-1839. “Lightweight offload engines for worklist management and worklist-directed prefetching.” 2018. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/68554.

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Author name may be incomplete

MLA Handbook (7th Edition):

-5112-1839. “Lightweight offload engines for worklist management and worklist-directed prefetching.” 2018. Web. 24 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-5112-1839. Lightweight offload engines for worklist management and worklist-directed prefetching. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2018. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/68554.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-5112-1839. Lightweight offload engines for worklist management and worklist-directed prefetching. [Doctoral Dissertation]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/68554

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Author name may be incomplete

24. Hung, Wei-Lun. Asynchronous automatic-signal monitors with multi-object synchronization.

Degree: PhD, Electrical and Computer engineering, 2016, University of Texas – Austin

 One of the fundamental problems in parallel programming is that there is no simple programming paradigm that provides mutual exclusion and synchronization with efficient implementation… (more)

Subjects/Keywords: Automatic signal; Implicit signal; Monitor; Synchronization; Concurrency; Parallel programming

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APA (6th Edition):

Hung, W. (2016). Asynchronous automatic-signal monitors with multi-object synchronization. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46269

Chicago Manual of Style (16th Edition):

Hung, Wei-Lun. “Asynchronous automatic-signal monitors with multi-object synchronization.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/46269.

MLA Handbook (7th Edition):

Hung, Wei-Lun. “Asynchronous automatic-signal monitors with multi-object synchronization.” 2016. Web. 24 Jan 2021.

Vancouver:

Hung W. Asynchronous automatic-signal monitors with multi-object synchronization. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/46269.

Council of Science Editors:

Hung W. Asynchronous automatic-signal monitors with multi-object synchronization. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/46269


University of Texas – Austin

25. Kim, Sangman. Networking abstractions for GPU programs.

Degree: PhD, Computer Sciences, 2015, University of Texas – Austin

 Graphics Processing Units (GPUs) are becoming major general-purpose computing hardware for high-performance parallel computation. Despite their general computation capability and impressive performance, GPUs still lack… (more)

Subjects/Keywords: GPU; Operating systems; Network; Socket; RDMA; CUDA; Infiniband

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APA (6th Edition):

Kim, S. (2015). Networking abstractions for GPU programs. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46765

Chicago Manual of Style (16th Edition):

Kim, Sangman. “Networking abstractions for GPU programs.” 2015. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/46765.

MLA Handbook (7th Edition):

Kim, Sangman. “Networking abstractions for GPU programs.” 2015. Web. 24 Jan 2021.

Vancouver:

Kim S. Networking abstractions for GPU programs. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2015. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/46765.

Council of Science Editors:

Kim S. Networking abstractions for GPU programs. [Doctoral Dissertation]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/46765

26. -6059-0490. Distributed tensor computations: formalizing distributions, redistributions, and algorithm derivation.

Degree: PhD, Computer science, 2015, University of Texas – Austin

 A goal of computer science is to develop practical methods to automate tasks that are otherwise too complex or tedious to perform manually. Complex tasks… (more)

Subjects/Keywords: High-performance computing; Parallel programming; Tensor computations

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APA (6th Edition):

-6059-0490. (2015). Distributed tensor computations: formalizing distributions, redistributions, and algorithm derivation. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/33276

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Author name may be incomplete

Chicago Manual of Style (16th Edition):

-6059-0490. “Distributed tensor computations: formalizing distributions, redistributions, and algorithm derivation.” 2015. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/33276.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-6059-0490. “Distributed tensor computations: formalizing distributions, redistributions, and algorithm derivation.” 2015. Web. 24 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-6059-0490. Distributed tensor computations: formalizing distributions, redistributions, and algorithm derivation. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2015. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/33276.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-6059-0490. Distributed tensor computations: formalizing distributions, redistributions, and algorithm derivation. [Doctoral Dissertation]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/33276

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Author name may be incomplete


University of Texas – Austin

27. -4372-6891. Predicate detection for parallel computations.

Degree: PhD, Electrical and Computer engineering, 2016, University of Texas – Austin

 One of the fundamental problems in runtime verification of parallel program is to check if a predicate could become true in any global state of… (more)

Subjects/Keywords: Predicate detection; Parallel computation; Reachability; Consistent global states; Global states enumeration

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APA (6th Edition):

-4372-6891. (2016). Predicate detection for parallel computations. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/44038

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Author name may be incomplete

Chicago Manual of Style (16th Edition):

-4372-6891. “Predicate detection for parallel computations.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/44038.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-4372-6891. “Predicate detection for parallel computations.” 2016. Web. 24 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-4372-6891. Predicate detection for parallel computations. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/44038.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-4372-6891. Predicate detection for parallel computations. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/44038

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Author name may be incomplete


University of Texas – Austin

28. -7595-5539. Practical fast matrix multiplication algorithms.

Degree: PhD, Computer Science, 2018, University of Texas – Austin

 Matrix multiplication is a core building block for numerous scientific computing and, more recently, machine learning applications. Strassen's algorithm, the original Fast Matrix Multiplication (FMM)… (more)

Subjects/Keywords: High performance computing; Matrix multiplication; Strassen's algorithm; Numerical algorithm; Mathematical software; Linear algebra library; BLAS; Performance model; Tensor contraction; GPU; Performance optimization; Machine learning; Parallel computing

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APA (6th Edition):

-7595-5539. (2018). Practical fast matrix multiplication algorithms. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/69013

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Author name may be incomplete

Chicago Manual of Style (16th Edition):

-7595-5539. “Practical fast matrix multiplication algorithms.” 2018. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/69013.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-7595-5539. “Practical fast matrix multiplication algorithms.” 2018. Web. 24 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-7595-5539. Practical fast matrix multiplication algorithms. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2018. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/69013.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-7595-5539. Practical fast matrix multiplication algorithms. [Doctoral Dissertation]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/69013

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Author name may be incomplete


University of Texas – Austin

29. Hassaan, Muhammad Amber. Parallelization of ordered irregular algorithms.

Degree: PhD, Electrical and Computer engineering, 2016, University of Texas – Austin

 Parallel computing hardware is ubiquitous, ranging from cell-phones with multiple cores to super-computers with hundreds of thousands of cores. Applications need to take advantage of… (more)

Subjects/Keywords: Ordered; Irregular; Parallelization; Runtime; Galois; Kinetic Dependence Graph; Dependence graph; Parallel languages

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APA (6th Edition):

Hassaan, M. A. (2016). Parallelization of ordered irregular algorithms. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46175

Chicago Manual of Style (16th Edition):

Hassaan, Muhammad Amber. “Parallelization of ordered irregular algorithms.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/46175.

MLA Handbook (7th Edition):

Hassaan, Muhammad Amber. “Parallelization of ordered irregular algorithms.” 2016. Web. 24 Jan 2021.

Vancouver:

Hassaan MA. Parallelization of ordered irregular algorithms. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/46175.

Council of Science Editors:

Hassaan MA. Parallelization of ordered irregular algorithms. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/46175

30. Chauhan, Himanshu. Algorithms for analyzing parallel computations.

Degree: PhD, Electrical and Computer Engineering, 2018, University of Texas – Austin

 Predicate detection is a powerful technique to verify parallel programs. Verifying correctness of programs using this technique involves two steps: first we create a partial… (more)

Subjects/Keywords: Algorithms; Theory; Distributed computing; Verification; Predication detection

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APA (6th Edition):

Chauhan, H. (2018). Algorithms for analyzing parallel computations. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63631

Chicago Manual of Style (16th Edition):

Chauhan, Himanshu. “Algorithms for analyzing parallel computations.” 2018. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/63631.

MLA Handbook (7th Edition):

Chauhan, Himanshu. “Algorithms for analyzing parallel computations.” 2018. Web. 24 Jan 2021.

Vancouver:

Chauhan H. Algorithms for analyzing parallel computations. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2018. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/63631.

Council of Science Editors:

Chauhan H. Algorithms for analyzing parallel computations. [Doctoral Dissertation]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/63631

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