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You searched for subject:(sparse matrix vector multiply). Showing records 1 – 30 of 13510 total matches.

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Colorado State University

1. Dinkins, Stephanie. Model for predicting the performance of sparse matrix vector multiply (SpMV) using memory bandwidth requirements and data locality, A.

Degree: MS(M.S.), Computer Science, 2012, Colorado State University

Sparse matrix vector multiply (SpMV) is an important computation that is used in many scientific and structural engineering applications. Sparse computations like SpMV require the… (more)

Subjects/Keywords: data locality; Manhattan distance; performance model; sparse matrices; sparse matrix vector multiply; SpMV

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

APA (6th Edition):

Dinkins, S. (2012). Model for predicting the performance of sparse matrix vector multiply (SpMV) using memory bandwidth requirements and data locality, A. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/65303

Chicago Manual of Style (16th Edition):

Dinkins, Stephanie. “Model for predicting the performance of sparse matrix vector multiply (SpMV) using memory bandwidth requirements and data locality, A.” 2012. Masters Thesis, Colorado State University. Accessed April 11, 2021. http://hdl.handle.net/10217/65303.

MLA Handbook (7th Edition):

Dinkins, Stephanie. “Model for predicting the performance of sparse matrix vector multiply (SpMV) using memory bandwidth requirements and data locality, A.” 2012. Web. 11 Apr 2021.

Vancouver:

Dinkins S. Model for predicting the performance of sparse matrix vector multiply (SpMV) using memory bandwidth requirements and data locality, A. [Internet] [Masters thesis]. Colorado State University; 2012. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10217/65303.

Council of Science Editors:

Dinkins S. Model for predicting the performance of sparse matrix vector multiply (SpMV) using memory bandwidth requirements and data locality, A. [Masters Thesis]. Colorado State University; 2012. Available from: http://hdl.handle.net/10217/65303


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 April 11, 2021. http://hdl.handle.net/10919/30260.

MLA Handbook (7th Edition):

Belgin, Mehmet. “Structure-based Optimizations for Sparse Matrix-Vector Multiply.” 2010. Web. 11 Apr 2021.

Vancouver:

Belgin M. Structure-based Optimizations for Sparse Matrix-Vector Multiply. [Internet] [Doctoral dissertation]. Virginia Tech; 2010. [cited 2021 Apr 11]. 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


Universiteit Utrecht

3. Kurt, H. Improving the Mondriaan vector distribution.

Degree: 2016, Universiteit Utrecht

 Mondriaan is a hypergraph based matrix partitioner, used to distribute the matrix and vectors in parallel sparse matrix-vector multiplication (SpMV) when calculating the product u=Av.… (more)

Subjects/Keywords: mondriaan; parallel algorithms; sparse matrix vector multiplication; vector distribution

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APA (6th Edition):

Kurt, H. (2016). Improving the Mondriaan vector distribution. (Masters Thesis). Universiteit Utrecht. Retrieved from http://dspace.library.uu.nl:8080/handle/1874/327906

Chicago Manual of Style (16th Edition):

Kurt, H. “Improving the Mondriaan vector distribution.” 2016. Masters Thesis, Universiteit Utrecht. Accessed April 11, 2021. http://dspace.library.uu.nl:8080/handle/1874/327906.

MLA Handbook (7th Edition):

Kurt, H. “Improving the Mondriaan vector distribution.” 2016. Web. 11 Apr 2021.

Vancouver:

Kurt H. Improving the Mondriaan vector distribution. [Internet] [Masters thesis]. Universiteit Utrecht; 2016. [cited 2021 Apr 11]. Available from: http://dspace.library.uu.nl:8080/handle/1874/327906.

Council of Science Editors:

Kurt H. Improving the Mondriaan vector distribution. [Masters Thesis]. Universiteit Utrecht; 2016. Available from: http://dspace.library.uu.nl:8080/handle/1874/327906


Indian Institute of Science

4. Ramesh, Chinthala. Hardware-Software Co-Design Accelerators for Sparse BLAS.

Degree: PhD, Engineering, 2019, Indian Institute of Science

Sparse Basic Linear Algebra Subroutines (Sparse BLAS) is an important library. Sparse BLAS includes three levels of subroutines. Level 1, Level2 and Level 3 Sparse(more)

Subjects/Keywords: Sparse Matrix Storage Formats; Hardware-Software Codesign Accelerators; Sparse BLAS; Hardware Accelerator; Sawtooth Compressed Row Storage; Sparse Vector Vector Multiplication; Sparse Matrix Matrix Multiplication; Sparse Matrix Vector Multiplication; Compressed Row Storage; Sparse Basic Linear Algebra Subroutines; SpMV Multiplication; SpMM Multiplication; Nano Science and Engineering

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APA (6th Edition):

Ramesh, C. (2019). Hardware-Software Co-Design Accelerators for Sparse BLAS. (Doctoral Dissertation). Indian Institute of Science. Retrieved from http://etd.iisc.ac.in/handle/2005/4276

Chicago Manual of Style (16th Edition):

Ramesh, Chinthala. “Hardware-Software Co-Design Accelerators for Sparse BLAS.” 2019. Doctoral Dissertation, Indian Institute of Science. Accessed April 11, 2021. http://etd.iisc.ac.in/handle/2005/4276.

MLA Handbook (7th Edition):

Ramesh, Chinthala. “Hardware-Software Co-Design Accelerators for Sparse BLAS.” 2019. Web. 11 Apr 2021.

Vancouver:

Ramesh C. Hardware-Software Co-Design Accelerators for Sparse BLAS. [Internet] [Doctoral dissertation]. Indian Institute of Science; 2019. [cited 2021 Apr 11]. Available from: http://etd.iisc.ac.in/handle/2005/4276.

Council of Science Editors:

Ramesh C. Hardware-Software Co-Design Accelerators for Sparse BLAS. [Doctoral Dissertation]. Indian Institute of Science; 2019. Available from: http://etd.iisc.ac.in/handle/2005/4276


Penn State University

5. Kestur Vyasa Prasanna, Srinidhi. Domain-specific Accelerators on Reconfigurable Platforms.

Degree: 2012, Penn State University

 With the increasing number of transistors available on a chip, microprocessors have evolved from large monolithic cores to multiple cores on a chip. However, to… (more)

Subjects/Keywords: accelerators; NuFFT; FPGA; N-body problem; matrix vector; sparse; saliency; HMAX; attention; recognition; neuromorphic; vision

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APA (6th Edition):

Kestur Vyasa Prasanna, S. (2012). Domain-specific Accelerators on Reconfigurable Platforms. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/13147

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Kestur Vyasa Prasanna, Srinidhi. “Domain-specific Accelerators on Reconfigurable Platforms.” 2012. Thesis, Penn State University. Accessed April 11, 2021. https://submit-etda.libraries.psu.edu/catalog/13147.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Kestur Vyasa Prasanna, Srinidhi. “Domain-specific Accelerators on Reconfigurable Platforms.” 2012. Web. 11 Apr 2021.

Vancouver:

Kestur Vyasa Prasanna S. Domain-specific Accelerators on Reconfigurable Platforms. [Internet] [Thesis]. Penn State University; 2012. [cited 2021 Apr 11]. Available from: https://submit-etda.libraries.psu.edu/catalog/13147.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kestur Vyasa Prasanna S. Domain-specific Accelerators on Reconfigurable Platforms. [Thesis]. Penn State University; 2012. Available from: https://submit-etda.libraries.psu.edu/catalog/13147

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Delft University of Technology

6. Stathis, P.T. Sparse Matrix Vector Processing Formats.

Degree: 2004, Delft University of Technology

 In this dissertation we have identified vector processing shortcomings related to the efficient storing and processing of sparse matrices. To alleviate existent problems we propose… (more)

Subjects/Keywords: vector processor; sparse matrix; storage formats

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APA (6th Edition):

Stathis, P. T. (2004). Sparse Matrix Vector Processing Formats. (Doctoral Dissertation). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:51b11f1c-699a-42f4-9373-b5c9697fde74 ; urn:NBN:nl:ui:24-uuid:51b11f1c-699a-42f4-9373-b5c9697fde74 ; urn:NBN:nl:ui:24-uuid:51b11f1c-699a-42f4-9373-b5c9697fde74 ; http://resolver.tudelft.nl/uuid:51b11f1c-699a-42f4-9373-b5c9697fde74

Chicago Manual of Style (16th Edition):

Stathis, P T. “Sparse Matrix Vector Processing Formats.” 2004. Doctoral Dissertation, Delft University of Technology. Accessed April 11, 2021. http://resolver.tudelft.nl/uuid:51b11f1c-699a-42f4-9373-b5c9697fde74 ; urn:NBN:nl:ui:24-uuid:51b11f1c-699a-42f4-9373-b5c9697fde74 ; urn:NBN:nl:ui:24-uuid:51b11f1c-699a-42f4-9373-b5c9697fde74 ; http://resolver.tudelft.nl/uuid:51b11f1c-699a-42f4-9373-b5c9697fde74.

MLA Handbook (7th Edition):

Stathis, P T. “Sparse Matrix Vector Processing Formats.” 2004. Web. 11 Apr 2021.

Vancouver:

Stathis PT. Sparse Matrix Vector Processing Formats. [Internet] [Doctoral dissertation]. Delft University of Technology; 2004. [cited 2021 Apr 11]. Available from: http://resolver.tudelft.nl/uuid:51b11f1c-699a-42f4-9373-b5c9697fde74 ; urn:NBN:nl:ui:24-uuid:51b11f1c-699a-42f4-9373-b5c9697fde74 ; urn:NBN:nl:ui:24-uuid:51b11f1c-699a-42f4-9373-b5c9697fde74 ; http://resolver.tudelft.nl/uuid:51b11f1c-699a-42f4-9373-b5c9697fde74.

Council of Science Editors:

Stathis PT. Sparse Matrix Vector Processing Formats. [Doctoral Dissertation]. Delft University of Technology; 2004. Available from: http://resolver.tudelft.nl/uuid:51b11f1c-699a-42f4-9373-b5c9697fde74 ; urn:NBN:nl:ui:24-uuid:51b11f1c-699a-42f4-9373-b5c9697fde74 ; urn:NBN:nl:ui:24-uuid:51b11f1c-699a-42f4-9373-b5c9697fde74 ; http://resolver.tudelft.nl/uuid:51b11f1c-699a-42f4-9373-b5c9697fde74


University of Illinois – Urbana-Champaign

7. Ravi, Vishal Jagannath. Automated methods for checking differential privacy.

Degree: MS, Computer Science, 2019, University of Illinois – Urbana-Champaign

 Differential privacy is a de facto standard for statistical computations over databases that contain private data. The strength of differential privacy lies in a rigorous… (more)

Subjects/Keywords: differential privacy; sparse vector

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APA (6th Edition):

Ravi, V. J. (2019). Automated methods for checking differential privacy. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/104913

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ravi, Vishal Jagannath. “Automated methods for checking differential privacy.” 2019. Thesis, University of Illinois – Urbana-Champaign. Accessed April 11, 2021. http://hdl.handle.net/2142/104913.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ravi, Vishal Jagannath. “Automated methods for checking differential privacy.” 2019. Web. 11 Apr 2021.

Vancouver:

Ravi VJ. Automated methods for checking differential privacy. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2019. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/2142/104913.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ravi VJ. Automated methods for checking differential privacy. [Thesis]. University of Illinois – Urbana-Champaign; 2019. Available from: http://hdl.handle.net/2142/104913

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

8. Ross, Christine Anne Haines. Accelerating induction machine finite-element simulation with parallel processing.

Degree: MS, Electrical & Computer Engineering, 2015, University of Illinois – Urbana-Champaign

 Finite element analysis used for detailed electromagnetic analysis and design of electric machines is computationally intensive. A means of accelerating two-dimensional transient finite element analysis,… (more)

Subjects/Keywords: finite element; simulation; finite; element; MATLAB; Graphics Processing Unit (GPU); parallel; parallel; processing; linear; nonlinear; transient; eddy current; eddy; induction; Machine; induction machine; electrical machine; speedup; electromagnetic; Compute Unified Device Architecture (CUDA); sparse matrix-vector multiplication; Sparse Matrix-vector Multiply (SpMV); Krylov; iterative solver; Finite Element Method (FEM); Finite Element Analysis (FEA); Galerkin

matrix A is sparse, b is a vector, and the system is solved for the vector x. For the sparse… …depends on the number and ordering of nonzero entries in the matrix. 16 Sparse iterative… …parallel programming to reduce the simulation time. 2 CHAPTER 2 MAGNETIC VECTOR POTENTIAL… …FORMULATION AND FINITE ELEMENT IMPLEMENTATION 2.1 Magnetic Vector Potential Formulation The… …expressed as 3 J = Js + σ E +σ v × B (2.8) The magnetic vector potential A is used… 

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APA (6th Edition):

Ross, C. A. H. (2015). Accelerating induction machine finite-element simulation with parallel processing. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/88070

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ross, Christine Anne Haines. “Accelerating induction machine finite-element simulation with parallel processing.” 2015. Thesis, University of Illinois – Urbana-Champaign. Accessed April 11, 2021. http://hdl.handle.net/2142/88070.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ross, Christine Anne Haines. “Accelerating induction machine finite-element simulation with parallel processing.” 2015. Web. 11 Apr 2021.

Vancouver:

Ross CAH. Accelerating induction machine finite-element simulation with parallel processing. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2015. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/2142/88070.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ross CAH. Accelerating induction machine finite-element simulation with parallel processing. [Thesis]. University of Illinois – Urbana-Champaign; 2015. Available from: http://hdl.handle.net/2142/88070

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Universidade do Estado do Rio de Janeiro

9. Daniel Estrela Lima Fonseca. Comparação do desempenho spMv entre formatos de armazenamento de matrizes esparsas provenientes do método AIM de simulação de reservatórios.

Degree: Master, 2016, Universidade do Estado do Rio de Janeiro

O presente trabalho faz uma avaliação de desempenho da multiplicação matriz esparsa por vetor denso (spMv), comparando dois formatos de armazenamento para as matrizes esparsas… (more)

Subjects/Keywords: Engenharia Mecânica; Matriz esparsa; Multiplicação matriz vetor; Simulação de reservatórios; Diferenças finitas; Mechanical Engineering; Sparse matrix; Matrix vector multiplication; Reservoir Simulation; Finite diferences; ENGENHARIA MECANICA

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APA (6th Edition):

Fonseca, D. E. L. (2016). Comparação do desempenho spMv entre formatos de armazenamento de matrizes esparsas provenientes do método AIM de simulação de reservatórios. (Masters Thesis). Universidade do Estado do Rio de Janeiro. Retrieved from http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=11153 ;

Chicago Manual of Style (16th Edition):

Fonseca, Daniel Estrela Lima. “Comparação do desempenho spMv entre formatos de armazenamento de matrizes esparsas provenientes do método AIM de simulação de reservatórios.” 2016. Masters Thesis, Universidade do Estado do Rio de Janeiro. Accessed April 11, 2021. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=11153 ;.

MLA Handbook (7th Edition):

Fonseca, Daniel Estrela Lima. “Comparação do desempenho spMv entre formatos de armazenamento de matrizes esparsas provenientes do método AIM de simulação de reservatórios.” 2016. Web. 11 Apr 2021.

Vancouver:

Fonseca DEL. Comparação do desempenho spMv entre formatos de armazenamento de matrizes esparsas provenientes do método AIM de simulação de reservatórios. [Internet] [Masters thesis]. Universidade do Estado do Rio de Janeiro; 2016. [cited 2021 Apr 11]. Available from: http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=11153 ;.

Council of Science Editors:

Fonseca DEL. Comparação do desempenho spMv entre formatos de armazenamento de matrizes esparsas provenientes do método AIM de simulação de reservatórios. [Masters Thesis]. Universidade do Estado do Rio de Janeiro; 2016. Available from: http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=11153 ;


Texas A&M University

10. Belsare, Aditya Sanjay. Sparse LU Factorization for Large Circuit Matrices on Heterogenous Parallel Computing Platforms.

Degree: MS, Computer Engineering, 2014, Texas A&M University

 Direct sparse solvers are traditionally known to be robust, yet difficult to parallelize. In the context of circuit simulators, they present an important bottleneck where… (more)

Subjects/Keywords: Sparse matrix solver; LU Factorization

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APA (6th Edition):

Belsare, A. S. (2014). Sparse LU Factorization for Large Circuit Matrices on Heterogenous Parallel Computing Platforms. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/153210

Chicago Manual of Style (16th Edition):

Belsare, Aditya Sanjay. “Sparse LU Factorization for Large Circuit Matrices on Heterogenous Parallel Computing Platforms.” 2014. Masters Thesis, Texas A&M University. Accessed April 11, 2021. http://hdl.handle.net/1969.1/153210.

MLA Handbook (7th Edition):

Belsare, Aditya Sanjay. “Sparse LU Factorization for Large Circuit Matrices on Heterogenous Parallel Computing Platforms.” 2014. Web. 11 Apr 2021.

Vancouver:

Belsare AS. Sparse LU Factorization for Large Circuit Matrices on Heterogenous Parallel Computing Platforms. [Internet] [Masters thesis]. Texas A&M University; 2014. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/1969.1/153210.

Council of Science Editors:

Belsare AS. Sparse LU Factorization for Large Circuit Matrices on Heterogenous Parallel Computing Platforms. [Masters Thesis]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/153210


Texas A&M University

11. Hoxha, Dielli. Sparse Matrices and Summa Matrix Multiplication Algorithm in STAPL Matrix Framework.

Degree: MS, Computer Engineering, 2016, Texas A&M University

 Applications of matrices are found in most scientific fields, such as physics, computer graphics, numerical analysis, etc. The high applicability of matrix algorithms and representations… (more)

Subjects/Keywords: Parallel Computing; Sparse Matrix

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APA (6th Edition):

Hoxha, D. (2016). Sparse Matrices and Summa Matrix Multiplication Algorithm in STAPL Matrix Framework. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/157157

Chicago Manual of Style (16th Edition):

Hoxha, Dielli. “Sparse Matrices and Summa Matrix Multiplication Algorithm in STAPL Matrix Framework.” 2016. Masters Thesis, Texas A&M University. Accessed April 11, 2021. http://hdl.handle.net/1969.1/157157.

MLA Handbook (7th Edition):

Hoxha, Dielli. “Sparse Matrices and Summa Matrix Multiplication Algorithm in STAPL Matrix Framework.” 2016. Web. 11 Apr 2021.

Vancouver:

Hoxha D. Sparse Matrices and Summa Matrix Multiplication Algorithm in STAPL Matrix Framework. [Internet] [Masters thesis]. Texas A&M University; 2016. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/1969.1/157157.

Council of Science Editors:

Hoxha D. Sparse Matrices and Summa Matrix Multiplication Algorithm in STAPL Matrix Framework. [Masters Thesis]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/157157


Texas State University – San Marcos

12. Chaudhary, Anjani. Conversion of Sparse Matrix to Band Matrix Using FPGA for High-Performance Computing.

Degree: MS, Engineering, 2020, Texas State University – San Marcos

 Low power and high computation speed with less memory storage are essential for a real-time scientific computational application. Applications such as image processing, power system,… (more)

Subjects/Keywords: Sparse Matrix; Band Matrix; RCM algorithm

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APA (6th Edition):

Chaudhary, A. (2020). Conversion of Sparse Matrix to Band Matrix Using FPGA for High-Performance Computing. (Masters Thesis). Texas State University – San Marcos. Retrieved from https://digital.library.txstate.edu/handle/10877/13033

Chicago Manual of Style (16th Edition):

Chaudhary, Anjani. “Conversion of Sparse Matrix to Band Matrix Using FPGA for High-Performance Computing.” 2020. Masters Thesis, Texas State University – San Marcos. Accessed April 11, 2021. https://digital.library.txstate.edu/handle/10877/13033.

MLA Handbook (7th Edition):

Chaudhary, Anjani. “Conversion of Sparse Matrix to Band Matrix Using FPGA for High-Performance Computing.” 2020. Web. 11 Apr 2021.

Vancouver:

Chaudhary A. Conversion of Sparse Matrix to Band Matrix Using FPGA for High-Performance Computing. [Internet] [Masters thesis]. Texas State University – San Marcos; 2020. [cited 2021 Apr 11]. Available from: https://digital.library.txstate.edu/handle/10877/13033.

Council of Science Editors:

Chaudhary A. Conversion of Sparse Matrix to Band Matrix Using FPGA for High-Performance Computing. [Masters Thesis]. Texas State University – San Marcos; 2020. Available from: https://digital.library.txstate.edu/handle/10877/13033


Iowa State University

13. Townsend, Kevin Rice. Computing SpMV on FPGAs.

Degree: 2016, Iowa State University

 There are hundreds of papers on accelerating sparse matrix vector multiplication (SpMV), however, only a handful target FPGAs. Some claim that FPGAs inherently perform inferiorly… (more)

Subjects/Keywords: Computer Engineering (Computing and Networking Systems); Computer Engineering; Computing and Networking Systems; FPGA; High Performance Reconfigurable Computing; Sparse Matrix Vector Multiplication; SpMV; Computer Engineering

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APA (6th Edition):

Townsend, K. R. (2016). Computing SpMV on FPGAs. (Thesis). Iowa State University. Retrieved from https://lib.dr.iastate.edu/etd/15227

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Townsend, Kevin Rice. “Computing SpMV on FPGAs.” 2016. Thesis, Iowa State University. Accessed April 11, 2021. https://lib.dr.iastate.edu/etd/15227.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Townsend, Kevin Rice. “Computing SpMV on FPGAs.” 2016. Web. 11 Apr 2021.

Vancouver:

Townsend KR. Computing SpMV on FPGAs. [Internet] [Thesis]. Iowa State University; 2016. [cited 2021 Apr 11]. Available from: https://lib.dr.iastate.edu/etd/15227.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Townsend KR. Computing SpMV on FPGAs. [Thesis]. Iowa State University; 2016. Available from: https://lib.dr.iastate.edu/etd/15227

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Delft University of Technology

14. Taouil, M. (author). A hardware Accelerator for the OpenFOAM Sparse Matrix-Vector Product.

Degree: 2009, Delft University of Technology

One of the key kernels in scientific applications is the Sparse Matrix Vector Multiplication (SMVM). Profiling OpenFOAM, a sophisticated scientific Computational Fluid Dynamics tool, proved… (more)

Subjects/Keywords: FPGA; Double Precision Floating Point; Sparse Matrix dense Vector Product; OpenFOAM

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APA (6th Edition):

Taouil, M. (. (2009). A hardware Accelerator for the OpenFOAM Sparse Matrix-Vector Product. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:ce583533-45ea-4237-b18d-fe31272ea1ee

Chicago Manual of Style (16th Edition):

Taouil, M (author). “A hardware Accelerator for the OpenFOAM Sparse Matrix-Vector Product.” 2009. Masters Thesis, Delft University of Technology. Accessed April 11, 2021. http://resolver.tudelft.nl/uuid:ce583533-45ea-4237-b18d-fe31272ea1ee.

MLA Handbook (7th Edition):

Taouil, M (author). “A hardware Accelerator for the OpenFOAM Sparse Matrix-Vector Product.” 2009. Web. 11 Apr 2021.

Vancouver:

Taouil M(. A hardware Accelerator for the OpenFOAM Sparse Matrix-Vector Product. [Internet] [Masters thesis]. Delft University of Technology; 2009. [cited 2021 Apr 11]. Available from: http://resolver.tudelft.nl/uuid:ce583533-45ea-4237-b18d-fe31272ea1ee.

Council of Science Editors:

Taouil M(. A hardware Accelerator for the OpenFOAM Sparse Matrix-Vector Product. [Masters Thesis]. Delft University of Technology; 2009. Available from: http://resolver.tudelft.nl/uuid:ce583533-45ea-4237-b18d-fe31272ea1ee

15. Black Silva, Edgar. Sparse matrix-vector multiplication by specialization.

Degree: MS, 0112, 2013, University of Illinois – Urbana-Champaign

 Program specialization is the process of generating optimized programs based on available inputs. It is particularly applicable when some input data are used repeatedly while… (more)

Subjects/Keywords: sparse matrix-vector multiplication; program specialization; run-time code generation.

…performing sparse matrix–dense vector multiplication, 2 including methods that are specialized… …Unfolding The simplest sparse matrix-vector multiplication method is to create a straightline… …vector multiplication by specialization relative to the matrix M , using matrices of… …apply in general to sparse matrices of the kind found in the Matrix Market [5] or… …the University of Florida Sparse Matrix Collection [6]. The structure of the… 

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APA (6th Edition):

Black Silva, E. (2013). Sparse matrix-vector multiplication by specialization. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/45518

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Black Silva, Edgar. “Sparse matrix-vector multiplication by specialization.” 2013. Thesis, University of Illinois – Urbana-Champaign. Accessed April 11, 2021. http://hdl.handle.net/2142/45518.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Black Silva, Edgar. “Sparse matrix-vector multiplication by specialization.” 2013. Web. 11 Apr 2021.

Vancouver:

Black Silva E. Sparse matrix-vector multiplication by specialization. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2013. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/2142/45518.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Black Silva E. Sparse matrix-vector multiplication by specialization. [Thesis]. University of Illinois – Urbana-Champaign; 2013. Available from: http://hdl.handle.net/2142/45518

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Southern California

16. Morris, Gerald Roger. Mapping sparse matrix scientific applications onto FPGA-augmented reconfigurable supercomputers.

Degree: PhD, Electrical Engineering, 2006, University of Southern California

 The large capacity of field programmable gate arrays (FPGAs) has prompted researchers to map computational kernels onto FPGAs. In some instances, these kernels achieve significant… (more)

Subjects/Keywords: reconfigurable computer; sparse matrix; Jacobi method; FPGA; conjugate gradient; vector reduction

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APA (6th Edition):

Morris, G. R. (2006). Mapping sparse matrix scientific applications onto FPGA-augmented reconfigurable supercomputers. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/29573/rec/3948

Chicago Manual of Style (16th Edition):

Morris, Gerald Roger. “Mapping sparse matrix scientific applications onto FPGA-augmented reconfigurable supercomputers.” 2006. Doctoral Dissertation, University of Southern California. Accessed April 11, 2021. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/29573/rec/3948.

MLA Handbook (7th Edition):

Morris, Gerald Roger. “Mapping sparse matrix scientific applications onto FPGA-augmented reconfigurable supercomputers.” 2006. Web. 11 Apr 2021.

Vancouver:

Morris GR. Mapping sparse matrix scientific applications onto FPGA-augmented reconfigurable supercomputers. [Internet] [Doctoral dissertation]. University of Southern California; 2006. [cited 2021 Apr 11]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/29573/rec/3948.

Council of Science Editors:

Morris GR. Mapping sparse matrix scientific applications onto FPGA-augmented reconfigurable supercomputers. [Doctoral Dissertation]. University of Southern California; 2006. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/29573/rec/3948

17. Flegar, Goran. Sparse Linear System Solvers on GPUs: Parallel Preconditioning, Workload Balancing, and Communication Reduction.

Degree: Programa de Doctorat en Informàtica, 2019, Universitat Jaume I

 Con el final de la ley de Dennard y el cercano fin de la ley de Moore, la comunidad en computación de altas prestaciones se… (more)

Subjects/Keywords: High Performance Computing; Graphics Processing Units; Adaptive Precision; Krylov Methods; Sparse Matrix-Vector Product; Preconditioning; Tecnologies de la informació i les comunicacions (TIC); 004

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APA (6th Edition):

Flegar, G. (2019). Sparse Linear System Solvers on GPUs: Parallel Preconditioning, Workload Balancing, and Communication Reduction. (Doctoral Dissertation). Universitat Jaume I. Retrieved from http://hdl.handle.net/10803/667096

Chicago Manual of Style (16th Edition):

Flegar, Goran. “Sparse Linear System Solvers on GPUs: Parallel Preconditioning, Workload Balancing, and Communication Reduction.” 2019. Doctoral Dissertation, Universitat Jaume I. Accessed April 11, 2021. http://hdl.handle.net/10803/667096.

MLA Handbook (7th Edition):

Flegar, Goran. “Sparse Linear System Solvers on GPUs: Parallel Preconditioning, Workload Balancing, and Communication Reduction.” 2019. Web. 11 Apr 2021.

Vancouver:

Flegar G. Sparse Linear System Solvers on GPUs: Parallel Preconditioning, Workload Balancing, and Communication Reduction. [Internet] [Doctoral dissertation]. Universitat Jaume I; 2019. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10803/667096.

Council of Science Editors:

Flegar G. Sparse Linear System Solvers on GPUs: Parallel Preconditioning, Workload Balancing, and Communication Reduction. [Doctoral Dissertation]. Universitat Jaume I; 2019. Available from: http://hdl.handle.net/10803/667096


Penn State University

18. Bangalore Srinivasmurthy, Sowmyalatha. Impact of soft errors on scientific simulations .

Degree: 2011, Penn State University

 The trends in computing processor technology are driving toward multicores through miniaturization that can pack many processors in a given chip area. This miniaturization has… (more)

Subjects/Keywords: sparse matrix; iterative linear solvers; soft error

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APA (6th Edition):

Bangalore Srinivasmurthy, S. (2011). Impact of soft errors on scientific simulations . (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/12404

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Bangalore Srinivasmurthy, Sowmyalatha. “Impact of soft errors on scientific simulations .” 2011. Thesis, Penn State University. Accessed April 11, 2021. https://submit-etda.libraries.psu.edu/catalog/12404.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Bangalore Srinivasmurthy, Sowmyalatha. “Impact of soft errors on scientific simulations .” 2011. Web. 11 Apr 2021.

Vancouver:

Bangalore Srinivasmurthy S. Impact of soft errors on scientific simulations . [Internet] [Thesis]. Penn State University; 2011. [cited 2021 Apr 11]. Available from: https://submit-etda.libraries.psu.edu/catalog/12404.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bangalore Srinivasmurthy S. Impact of soft errors on scientific simulations . [Thesis]. Penn State University; 2011. Available from: https://submit-etda.libraries.psu.edu/catalog/12404

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Delft University of Technology

19. Sigurbergsson, Bjorn (author). A Hardware/Software Co-designed Partitioning Algorithm of Sparse Matrix Vector Multiplication into Multiple Independent Streams for Parallel Processing.

Degree: 2018, Delft University of Technology

The trend of computing faster and more efficiently has been a driver for the computing industry since its beginning. However, it is increasingly difficult to… (more)

Subjects/Keywords: Big data; Sparse matrix; HLS; FPGA; Zynq

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

APA (6th Edition):

Sigurbergsson, B. (. (2018). A Hardware/Software Co-designed Partitioning Algorithm of Sparse Matrix Vector Multiplication into Multiple Independent Streams for Parallel Processing. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:92cbecec-aed8-40c6-b70c-c4ab7e8e548e

Chicago Manual of Style (16th Edition):

Sigurbergsson, Bjorn (author). “A Hardware/Software Co-designed Partitioning Algorithm of Sparse Matrix Vector Multiplication into Multiple Independent Streams for Parallel Processing.” 2018. Masters Thesis, Delft University of Technology. Accessed April 11, 2021. http://resolver.tudelft.nl/uuid:92cbecec-aed8-40c6-b70c-c4ab7e8e548e.

MLA Handbook (7th Edition):

Sigurbergsson, Bjorn (author). “A Hardware/Software Co-designed Partitioning Algorithm of Sparse Matrix Vector Multiplication into Multiple Independent Streams for Parallel Processing.” 2018. Web. 11 Apr 2021.

Vancouver:

Sigurbergsson B(. A Hardware/Software Co-designed Partitioning Algorithm of Sparse Matrix Vector Multiplication into Multiple Independent Streams for Parallel Processing. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Apr 11]. Available from: http://resolver.tudelft.nl/uuid:92cbecec-aed8-40c6-b70c-c4ab7e8e548e.

Council of Science Editors:

Sigurbergsson B(. A Hardware/Software Co-designed Partitioning Algorithm of Sparse Matrix Vector Multiplication into Multiple Independent Streams for Parallel Processing. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:92cbecec-aed8-40c6-b70c-c4ab7e8e548e


Virginia Tech

20. Kang, Xiaoning. Contributions to Large Covariance and Inverse Covariance Matrices Estimation.

Degree: PhD, Statistics, 2016, Virginia Tech

 Estimation of covariance matrix and its inverse is of great importance in multivariate statistics with broad applications such as dimension reduction, portfolio optimization, linear discriminant… (more)

Subjects/Keywords: Covariance matrix; modified Cholesky decomposition; sparse estimation

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APA (6th Edition):

Kang, X. (2016). Contributions to Large Covariance and Inverse Covariance Matrices Estimation. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/82150

Chicago Manual of Style (16th Edition):

Kang, Xiaoning. “Contributions to Large Covariance and Inverse Covariance Matrices Estimation.” 2016. Doctoral Dissertation, Virginia Tech. Accessed April 11, 2021. http://hdl.handle.net/10919/82150.

MLA Handbook (7th Edition):

Kang, Xiaoning. “Contributions to Large Covariance and Inverse Covariance Matrices Estimation.” 2016. Web. 11 Apr 2021.

Vancouver:

Kang X. Contributions to Large Covariance and Inverse Covariance Matrices Estimation. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10919/82150.

Council of Science Editors:

Kang X. Contributions to Large Covariance and Inverse Covariance Matrices Estimation. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/82150


University of Illinois – Urbana-Champaign

21. Wolf, Michael M. Hypergraph-Based Combinatorial Optimization of Matrix-Vector Multiplication.

Degree: PhD, Computer Science, 2009, University of Illinois – Urbana-Champaign

 Combinatorial scientific computing plays an important enabling role in computational science, particularly in high performance scientific computing. In this thesis, we will describe our work… (more)

Subjects/Keywords: matrix-vector multiplication; hypergraphs; combinatorial optimization; parallel data distributions; finite elements; sparse matrix computations; combinatorial scientific computing

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

APA (6th Edition):

Wolf, M. M. (2009). Hypergraph-Based Combinatorial Optimization of Matrix-Vector Multiplication. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/13069

Chicago Manual of Style (16th Edition):

Wolf, Michael M. “Hypergraph-Based Combinatorial Optimization of Matrix-Vector Multiplication.” 2009. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed April 11, 2021. http://hdl.handle.net/2142/13069.

MLA Handbook (7th Edition):

Wolf, Michael M. “Hypergraph-Based Combinatorial Optimization of Matrix-Vector Multiplication.” 2009. Web. 11 Apr 2021.

Vancouver:

Wolf MM. Hypergraph-Based Combinatorial Optimization of Matrix-Vector Multiplication. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2009. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/2142/13069.

Council of Science Editors:

Wolf MM. Hypergraph-Based Combinatorial Optimization of Matrix-Vector Multiplication. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2009. Available from: http://hdl.handle.net/2142/13069


University of Lethbridge

22. University of Lethbridge. Faculty of Arts and Science. Bi-directional determination of sparse Jacobian matrices : algorithms and lower bounds .

Degree: 2015, University of Lethbridge

 Efficient estimation of large sparse Jacobian matrices is a requisite in many large-scale scientific and engineering problems. It is known that estimation of non-zeroes of… (more)

Subjects/Keywords: sparse matrix; Jacobian matrix; row and column compressions; bi-directional partitioning

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APA (6th Edition):

Science, U. o. L. F. o. A. a. (2015). Bi-directional determination of sparse Jacobian matrices : algorithms and lower bounds . (Thesis). University of Lethbridge. Retrieved from http://hdl.handle.net/10133/3760

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Science, University of Lethbridge. Faculty of Arts and. “Bi-directional determination of sparse Jacobian matrices : algorithms and lower bounds .” 2015. Thesis, University of Lethbridge. Accessed April 11, 2021. http://hdl.handle.net/10133/3760.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Science, University of Lethbridge. Faculty of Arts and. “Bi-directional determination of sparse Jacobian matrices : algorithms and lower bounds .” 2015. Web. 11 Apr 2021.

Vancouver:

Science UoLFoAa. Bi-directional determination of sparse Jacobian matrices : algorithms and lower bounds . [Internet] [Thesis]. University of Lethbridge; 2015. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10133/3760.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Science UoLFoAa. Bi-directional determination of sparse Jacobian matrices : algorithms and lower bounds . [Thesis]. University of Lethbridge; 2015. Available from: http://hdl.handle.net/10133/3760

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Georgia State University

23. Wu, Xiaolong. Optimizing Sparse Matrix-Matrix Multiplication on a Heterogeneous CPU-GPU Platform.

Degree: MS, Computer Science, 2015, Georgia State University

Sparse Matrix-Matrix multiplication (SpMM) is a fundamental operation over irregular data, which is widely used in graph algorithms, such as finding minimum spanning trees… (more)

Subjects/Keywords: Sparse matrix-matrix multiplication; Data locality; Pipelining; GPU

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APA (6th Edition):

Wu, X. (2015). Optimizing Sparse Matrix-Matrix Multiplication on a Heterogeneous CPU-GPU Platform. (Thesis). Georgia State University. Retrieved from https://scholarworks.gsu.edu/cs_theses/84

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wu, Xiaolong. “Optimizing Sparse Matrix-Matrix Multiplication on a Heterogeneous CPU-GPU Platform.” 2015. Thesis, Georgia State University. Accessed April 11, 2021. https://scholarworks.gsu.edu/cs_theses/84.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wu, Xiaolong. “Optimizing Sparse Matrix-Matrix Multiplication on a Heterogeneous CPU-GPU Platform.” 2015. Web. 11 Apr 2021.

Vancouver:

Wu X. Optimizing Sparse Matrix-Matrix Multiplication on a Heterogeneous CPU-GPU Platform. [Internet] [Thesis]. Georgia State University; 2015. [cited 2021 Apr 11]. Available from: https://scholarworks.gsu.edu/cs_theses/84.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wu X. Optimizing Sparse Matrix-Matrix Multiplication on a Heterogeneous CPU-GPU Platform. [Thesis]. Georgia State University; 2015. Available from: https://scholarworks.gsu.edu/cs_theses/84

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Tennessee – Knoxville

24. Peyton, Jonathan Lawrence. Programming Dense Linear Algebra Kernels on Vectorized Architectures.

Degree: MS, Computer Engineering, 2013, University of Tennessee – Knoxville

  The high performance computing (HPC) community is obsessed over the general matrix-matrix multiply (GEMM) routine. This obsession is not without reason. Most, if not… (more)

Subjects/Keywords: MIC; Vectorization; Linear Algebra; Matrix Multiply; Cholesky; Computer and Systems Architecture; Computer Engineering; Numerical Analysis and Scientific Computing

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APA (6th Edition):

Peyton, J. L. (2013). Programming Dense Linear Algebra Kernels on Vectorized Architectures. (Thesis). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_gradthes/1666

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Peyton, Jonathan Lawrence. “Programming Dense Linear Algebra Kernels on Vectorized Architectures.” 2013. Thesis, University of Tennessee – Knoxville. Accessed April 11, 2021. https://trace.tennessee.edu/utk_gradthes/1666.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Peyton, Jonathan Lawrence. “Programming Dense Linear Algebra Kernels on Vectorized Architectures.” 2013. Web. 11 Apr 2021.

Vancouver:

Peyton JL. Programming Dense Linear Algebra Kernels on Vectorized Architectures. [Internet] [Thesis]. University of Tennessee – Knoxville; 2013. [cited 2021 Apr 11]. Available from: https://trace.tennessee.edu/utk_gradthes/1666.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Peyton JL. Programming Dense Linear Algebra Kernels on Vectorized Architectures. [Thesis]. University of Tennessee – Knoxville; 2013. Available from: https://trace.tennessee.edu/utk_gradthes/1666

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

25. Karakasis, Vasileios. Βελτιστοποίηση του υπολογιστικού πυρήνα πολλαπλασιασμού αραιού πίνακα με διάνυσμα σε σύγχρονες πολυπύρηνες αρχιτεκτονικές υπολογιστών.

Degree: 2012, National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ)

This thesis focuses on the optimization of the Sparse Matrix-Vector Multiplication kernel (SpMV) for modern multicore architectures. We perform an in-depth performance analysis of the… (more)

Subjects/Keywords: Υπολογιστικά συστήματα υψηλών επιδόσεων; Επιστημονικές εφαρμογές; Πολλαπλασιασμός αραιού πίνακα με διάνυσμα; Πολυπύρηνες αρχιτεκτονικές; Συμπίεση δεδομένων; Ενεργειακή απόδοση; High performance computing; Scientific applications; Sparse matrix-vector multiplication; Multicore; Data compression; Energy-efficiency; SpMV; CSX; HPC

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APA (6th Edition):

Karakasis, V. (2012). Βελτιστοποίηση του υπολογιστικού πυρήνα πολλαπλασιασμού αραιού πίνακα με διάνυσμα σε σύγχρονες πολυπύρηνες αρχιτεκτονικές υπολογιστών. (Thesis). National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ). Retrieved from http://hdl.handle.net/10442/hedi/34819

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Karakasis, Vasileios. “Βελτιστοποίηση του υπολογιστικού πυρήνα πολλαπλασιασμού αραιού πίνακα με διάνυσμα σε σύγχρονες πολυπύρηνες αρχιτεκτονικές υπολογιστών.” 2012. Thesis, National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ). Accessed April 11, 2021. http://hdl.handle.net/10442/hedi/34819.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Karakasis, Vasileios. “Βελτιστοποίηση του υπολογιστικού πυρήνα πολλαπλασιασμού αραιού πίνακα με διάνυσμα σε σύγχρονες πολυπύρηνες αρχιτεκτονικές υπολογιστών.” 2012. Web. 11 Apr 2021.

Vancouver:

Karakasis V. Βελτιστοποίηση του υπολογιστικού πυρήνα πολλαπλασιασμού αραιού πίνακα με διάνυσμα σε σύγχρονες πολυπύρηνες αρχιτεκτονικές υπολογιστών. [Internet] [Thesis]. National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ); 2012. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10442/hedi/34819.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Karakasis V. Βελτιστοποίηση του υπολογιστικού πυρήνα πολλαπλασιασμού αραιού πίνακα με διάνυσμα σε σύγχρονες πολυπύρηνες αρχιτεκτονικές υπολογιστών. [Thesis]. National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ); 2012. Available from: http://hdl.handle.net/10442/hedi/34819

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Newcastle

26. Fitzpatrick, Chris. Firmwares for high-speed signal processing applications.

Degree: MPhil, 2016, University of Newcastle

Masters Research - Master of Philosophy (MPhil)

Matrix-vector multiplication is widely used in science and engineering. With the constant increase in data throughput rates, computing… (more)

Subjects/Keywords: VHDL; FPGA; matrix; vector; floating point; MAC

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APA (6th Edition):

Fitzpatrick, C. (2016). Firmwares for high-speed signal processing applications. (Masters Thesis). University of Newcastle. Retrieved from http://hdl.handle.net/1959.13/1312018

Chicago Manual of Style (16th Edition):

Fitzpatrick, Chris. “Firmwares for high-speed signal processing applications.” 2016. Masters Thesis, University of Newcastle. Accessed April 11, 2021. http://hdl.handle.net/1959.13/1312018.

MLA Handbook (7th Edition):

Fitzpatrick, Chris. “Firmwares for high-speed signal processing applications.” 2016. Web. 11 Apr 2021.

Vancouver:

Fitzpatrick C. Firmwares for high-speed signal processing applications. [Internet] [Masters thesis]. University of Newcastle; 2016. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/1959.13/1312018.

Council of Science Editors:

Fitzpatrick C. Firmwares for high-speed signal processing applications. [Masters Thesis]. University of Newcastle; 2016. Available from: http://hdl.handle.net/1959.13/1312018


Rice University

27. Luo, Shangyu. Adding Vector and Matrix Support to SimSQL.

Degree: MS, Engineering, 2016, Rice University

 In this thesis, I consider the problem of making linear algebra simple to use and efficient to run in a relational database management system. Relational… (more)

Subjects/Keywords: Vector/Matrix; Linear Algebra; RDBMS; SQL

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APA (6th Edition):

Luo, S. (2016). Adding Vector and Matrix Support to SimSQL. (Masters Thesis). Rice University. Retrieved from http://hdl.handle.net/1911/96227

Chicago Manual of Style (16th Edition):

Luo, Shangyu. “Adding Vector and Matrix Support to SimSQL.” 2016. Masters Thesis, Rice University. Accessed April 11, 2021. http://hdl.handle.net/1911/96227.

MLA Handbook (7th Edition):

Luo, Shangyu. “Adding Vector and Matrix Support to SimSQL.” 2016. Web. 11 Apr 2021.

Vancouver:

Luo S. Adding Vector and Matrix Support to SimSQL. [Internet] [Masters thesis]. Rice University; 2016. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/1911/96227.

Council of Science Editors:

Luo S. Adding Vector and Matrix Support to SimSQL. [Masters Thesis]. Rice University; 2016. Available from: http://hdl.handle.net/1911/96227


Penn State University

28. Kabir, Humayun. HIERARCHICAL SPARSE GRAPH COMPUTATIONS ON MULTICORE PLATFORMS.

Degree: 2018, Penn State University

 Graph analysis is widely used to study connectivity, centrality, community and path analysis of social networks, biological networks, communication networks and any interacting objects that… (more)

Subjects/Keywords: k-core; k-truss; multicore; sparse matrix; network analysis; graph analysis

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

APA (6th Edition):

Kabir, H. (2018). HIERARCHICAL SPARSE GRAPH COMPUTATIONS ON MULTICORE PLATFORMS. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/15185hzk134

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Kabir, Humayun. “HIERARCHICAL SPARSE GRAPH COMPUTATIONS ON MULTICORE PLATFORMS.” 2018. Thesis, Penn State University. Accessed April 11, 2021. https://submit-etda.libraries.psu.edu/catalog/15185hzk134.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Kabir, Humayun. “HIERARCHICAL SPARSE GRAPH COMPUTATIONS ON MULTICORE PLATFORMS.” 2018. Web. 11 Apr 2021.

Vancouver:

Kabir H. HIERARCHICAL SPARSE GRAPH COMPUTATIONS ON MULTICORE PLATFORMS. [Internet] [Thesis]. Penn State University; 2018. [cited 2021 Apr 11]. Available from: https://submit-etda.libraries.psu.edu/catalog/15185hzk134.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kabir H. HIERARCHICAL SPARSE GRAPH COMPUTATIONS ON MULTICORE PLATFORMS. [Thesis]. Penn State University; 2018. Available from: https://submit-etda.libraries.psu.edu/catalog/15185hzk134

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

29. bi, xiaofei. Compressed Sampling for High Frequency Receivers Applications.

Degree: Mathematics and Natural Sciences, 2011, University of Gävle

  In digital signal processing field, for recovering the signal without distortion, Shannon sampling theory must be fulfilled in the traditional signal sampling. However, in… (more)

Subjects/Keywords: Compressive Sampling (CS); sparse representation; measurement matrix; signal reconstruction.

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

APA (6th Edition):

bi, x. (2011). Compressed Sampling for High Frequency Receivers Applications. (Thesis). University of Gävle. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-10877

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

bi, xiaofei. “Compressed Sampling for High Frequency Receivers Applications.” 2011. Thesis, University of Gävle. Accessed April 11, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-10877.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

bi, xiaofei. “Compressed Sampling for High Frequency Receivers Applications.” 2011. Web. 11 Apr 2021.

Vancouver:

bi x. Compressed Sampling for High Frequency Receivers Applications. [Internet] [Thesis]. University of Gävle; 2011. [cited 2021 Apr 11]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-10877.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

bi x. Compressed Sampling for High Frequency Receivers Applications. [Thesis]. University of Gävle; 2011. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-10877

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

30. Yang, Tao. The gap between necessity and sufficiency for stability of sparse matrix systems: simulation studies.

Degree: MS, Electrical & Computer Engr, 2015, University of Illinois – Urbana-Champaign

Sparse matrix systems (SMSs) are potentially very useful for graph analysis and topological representations of interaction and communication among elements within a system. Such systems’… (more)

Subjects/Keywords: Sparse Matrix Systems

…the Motivation and Algorithms 3.1 Symmetric Sparse Matrix Systems As suggested above, the… …necessary condition is not able to guarantee that the sparse matrix system is stable. However, for… …of zeros in this symmetric sparse matrix system is less than or equal to the planned number… …zeros in this sparse matrix system is odd, there also will be an odd number of diagonal… …configuration of symmetric sparse matrix system will fail. Second, if there is only one available… 

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

APA (6th Edition):

Yang, T. (2015). The gap between necessity and sufficiency for stability of sparse matrix systems: simulation studies. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/78554

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Yang, Tao. “The gap between necessity and sufficiency for stability of sparse matrix systems: simulation studies.” 2015. Thesis, University of Illinois – Urbana-Champaign. Accessed April 11, 2021. http://hdl.handle.net/2142/78554.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Yang, Tao. “The gap between necessity and sufficiency for stability of sparse matrix systems: simulation studies.” 2015. Web. 11 Apr 2021.

Vancouver:

Yang T. The gap between necessity and sufficiency for stability of sparse matrix systems: simulation studies. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2015. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/2142/78554.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Yang T. The gap between necessity and sufficiency for stability of sparse matrix systems: simulation studies. [Thesis]. University of Illinois – Urbana-Champaign; 2015. Available from: http://hdl.handle.net/2142/78554

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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