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You searched for subject:(GPU memory systems). Showing records 1 – 8 of 8 total matches.

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University of Illinois – Urbana-Champaign

1. Alsop, Johnathan R. Specialization without complexity in heterogeneous memory systems.

Degree: PhD, Electrical & Computer Engr, 2018, University of Illinois – Urbana-Champaign

 The end of Dennard scaling and Moore's law has motivated a rise in the use of parallelism and hardware specialization in computer system design. Across… (more)

Subjects/Keywords: heterogeneous computing; coherence; consistency; memory systems; GPU

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APA (6th Edition):

Alsop, J. R. (2018). Specialization without complexity in heterogeneous memory systems. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/102480

Chicago Manual of Style (16th Edition):

Alsop, Johnathan R. “Specialization without complexity in heterogeneous memory systems.” 2018. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed March 04, 2021. http://hdl.handle.net/2142/102480.

MLA Handbook (7th Edition):

Alsop, Johnathan R. “Specialization without complexity in heterogeneous memory systems.” 2018. Web. 04 Mar 2021.

Vancouver:

Alsop JR. Specialization without complexity in heterogeneous memory systems. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2018. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/2142/102480.

Council of Science Editors:

Alsop JR. Specialization without complexity in heterogeneous memory systems. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2018. Available from: http://hdl.handle.net/2142/102480


University of Texas – Austin

2. Burden, Cassidy Aaron. Evaluating headroom for smart caching policies on GPUs.

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

 This report evaluates two distinct methods of improving the performance of GPU memory systems. Over the past semester, our research has focused on applying a… (more)

Subjects/Keywords: GPU; Hawkeye; Precleaning; Caching; Headroom; Cache replacement policy; GPU memory systems; Cache miss rates

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APA (6th Edition):

Burden, C. A. (2018). Evaluating headroom for smart caching policies on GPUs. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/65984

Chicago Manual of Style (16th Edition):

Burden, Cassidy Aaron. “Evaluating headroom for smart caching policies on GPUs.” 2018. Masters Thesis, University of Texas – Austin. Accessed March 04, 2021. http://hdl.handle.net/2152/65984.

MLA Handbook (7th Edition):

Burden, Cassidy Aaron. “Evaluating headroom for smart caching policies on GPUs.” 2018. Web. 04 Mar 2021.

Vancouver:

Burden CA. Evaluating headroom for smart caching policies on GPUs. [Internet] [Masters thesis]. University of Texas – Austin; 2018. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/2152/65984.

Council of Science Editors:

Burden CA. Evaluating headroom for smart caching policies on GPUs. [Masters Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/65984


Virginia Tech

3. Lee, Kenneth Sydney. Characterization and Exploitation of GPU Memory Systems.

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

 Graphics Processing Units (GPUs) are workhorses of modern performance due to their ability to achieve massive speedups on parallel applications. The massive number of threads… (more)

Subjects/Keywords: Data Transfer; Performance Modeling; GPGPU; APU; GPU; Memory Systems

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APA (6th Edition):

Lee, K. S. (2012). Characterization and Exploitation of GPU Memory Systems. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/34215

Chicago Manual of Style (16th Edition):

Lee, Kenneth Sydney. “Characterization and Exploitation of GPU Memory Systems.” 2012. Masters Thesis, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/34215.

MLA Handbook (7th Edition):

Lee, Kenneth Sydney. “Characterization and Exploitation of GPU Memory Systems.” 2012. Web. 04 Mar 2021.

Vancouver:

Lee KS. Characterization and Exploitation of GPU Memory Systems. [Internet] [Masters thesis]. Virginia Tech; 2012. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/34215.

Council of Science Editors:

Lee KS. Characterization and Exploitation of GPU Memory Systems. [Masters Thesis]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/34215


University of Illinois – Chicago

4. Ghiozzi, Fabio. Priority-Based Memory Access Scheduling for CPU-GPU Workloads.

Degree: 2015, University of Illinois – Chicago

 This thesis work is developed to design and implement a brand new Memory Access Scheduling Algorithm for CPU-GPU heterogeneous architectures. The ultimate goal is to… (more)

Subjects/Keywords: Heterogeneous Systems; Computer Architectures; CPU; GPU; Main Memory; Memory Controller; Memory Accesses Scheduling; Memory Scheduling Algorithm

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APA (6th Edition):

Ghiozzi, F. (2015). Priority-Based Memory Access Scheduling for CPU-GPU Workloads. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/19844

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):

Ghiozzi, Fabio. “Priority-Based Memory Access Scheduling for CPU-GPU Workloads.” 2015. Thesis, University of Illinois – Chicago. Accessed March 04, 2021. http://hdl.handle.net/10027/19844.

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

MLA Handbook (7th Edition):

Ghiozzi, Fabio. “Priority-Based Memory Access Scheduling for CPU-GPU Workloads.” 2015. Web. 04 Mar 2021.

Vancouver:

Ghiozzi F. Priority-Based Memory Access Scheduling for CPU-GPU Workloads. [Internet] [Thesis]. University of Illinois – Chicago; 2015. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10027/19844.

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

Council of Science Editors:

Ghiozzi F. Priority-Based Memory Access Scheduling for CPU-GPU Workloads. [Thesis]. University of Illinois – Chicago; 2015. Available from: http://hdl.handle.net/10027/19844

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


University of Edinburgh

5. Bogoychev, Nikolay Veselinov. Fast machine translation on parallel and massively parallel hardware.

Degree: PhD, 2019, University of Edinburgh

 Parallel systems have been widely adopted in the field of machine translation, because the raw computational power they offer is well suited to this computationally… (more)

Subjects/Keywords: machine translation systems; memory speed; machine translation; efficient algorithms; processing speed; phrase tables; GPU-based n-gram language model; optimized CPU implementation; Moses; Marian

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APA (6th Edition):

Bogoychev, N. V. (2019). Fast machine translation on parallel and massively parallel hardware. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/35886

Chicago Manual of Style (16th Edition):

Bogoychev, Nikolay Veselinov. “Fast machine translation on parallel and massively parallel hardware.” 2019. Doctoral Dissertation, University of Edinburgh. Accessed March 04, 2021. http://hdl.handle.net/1842/35886.

MLA Handbook (7th Edition):

Bogoychev, Nikolay Veselinov. “Fast machine translation on parallel and massively parallel hardware.” 2019. Web. 04 Mar 2021.

Vancouver:

Bogoychev NV. Fast machine translation on parallel and massively parallel hardware. [Internet] [Doctoral dissertation]. University of Edinburgh; 2019. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1842/35886.

Council of Science Editors:

Bogoychev NV. Fast machine translation on parallel and massively parallel hardware. [Doctoral Dissertation]. University of Edinburgh; 2019. Available from: http://hdl.handle.net/1842/35886

6. Rhu, Minsoo. Performance-efficient mechanisms for managing irregularity in throughput processors.

Degree: PhD, Electrical and Computer Engineering, 2014, University of Texas – Austin

 Recent graphics processing units (GPUs) have emerged as a promising platform for general purpose computing and have been shown to be very efficient in executing… (more)

Subjects/Keywords: Computer architecture; GPU; Graphics; Throughput processors; Memory systems

…applications with regular control and memory access behavior. Current GPU architectures primarily… …126 5.1.2 Limitation of Coarse-Grained Memory Systems . . . . . 126 xii 5.2 Designing a… …memory hierarchy. . . . . . . . . . . . 15 2.5 High-level overview of the baseline GPU… …I observe that this lack of locality consideration in memory systems leads to significant… …GPU control divergence. In the second half of the thesis, I observe that conventional memory… 

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APA (6th Edition):

Rhu, M. (2014). Performance-efficient mechanisms for managing irregularity in throughput processors. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/24926

Chicago Manual of Style (16th Edition):

Rhu, Minsoo. “Performance-efficient mechanisms for managing irregularity in throughput processors.” 2014. Doctoral Dissertation, University of Texas – Austin. Accessed March 04, 2021. http://hdl.handle.net/2152/24926.

MLA Handbook (7th Edition):

Rhu, Minsoo. “Performance-efficient mechanisms for managing irregularity in throughput processors.” 2014. Web. 04 Mar 2021.

Vancouver:

Rhu M. Performance-efficient mechanisms for managing irregularity in throughput processors. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2014. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/2152/24926.

Council of Science Editors:

Rhu M. Performance-efficient mechanisms for managing irregularity in throughput processors. [Doctoral Dissertation]. University of Texas – Austin; 2014. Available from: http://hdl.handle.net/2152/24926

7. Lopez, Florent. Task-based multifrontal QR solver for heterogeneous architectures : Solveur multifrontal QR à base de tâches pour architectures hétérogènes.

Degree: Docteur es, Sureté du logiciel et calcul haute preformance, 2015, Université Toulouse III – Paul Sabatier

Afin de s'adapter aux architectures multicoeurs et aux machines de plus en plus complexes, les modèles de programmations basés sur un parallélisme de tâche ont… (more)

Subjects/Keywords: Méthodes directes de résolution de systèmes linéaires; Méthode multifrontale; Multicœur; Moteurs d'exécutions; Ordonnancement, algorithmes d'ordonnancement sous contraintes mémoire; Architectures hétérogènes; Calcul haute performance; GPU; Sparse direct solvers; Multifrontal method; Multicores; Runtime systems; Scheduling; Memory-aware algorythms; Heterogeneous architectures; High-performance computing

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APA (6th Edition):

Lopez, F. (2015). Task-based multifrontal QR solver for heterogeneous architectures : Solveur multifrontal QR à base de tâches pour architectures hétérogènes. (Doctoral Dissertation). Université Toulouse III – Paul Sabatier. Retrieved from http://www.theses.fr/2015TOU30303

Chicago Manual of Style (16th Edition):

Lopez, Florent. “Task-based multifrontal QR solver for heterogeneous architectures : Solveur multifrontal QR à base de tâches pour architectures hétérogènes.” 2015. Doctoral Dissertation, Université Toulouse III – Paul Sabatier. Accessed March 04, 2021. http://www.theses.fr/2015TOU30303.

MLA Handbook (7th Edition):

Lopez, Florent. “Task-based multifrontal QR solver for heterogeneous architectures : Solveur multifrontal QR à base de tâches pour architectures hétérogènes.” 2015. Web. 04 Mar 2021.

Vancouver:

Lopez F. Task-based multifrontal QR solver for heterogeneous architectures : Solveur multifrontal QR à base de tâches pour architectures hétérogènes. [Internet] [Doctoral dissertation]. Université Toulouse III – Paul Sabatier; 2015. [cited 2021 Mar 04]. Available from: http://www.theses.fr/2015TOU30303.

Council of Science Editors:

Lopez F. Task-based multifrontal QR solver for heterogeneous architectures : Solveur multifrontal QR à base de tâches pour architectures hétérogènes. [Doctoral Dissertation]. Université Toulouse III – Paul Sabatier; 2015. Available from: http://www.theses.fr/2015TOU30303

8. Wang, Kaibo. Algorithmic and Software System Support to Accelerate Data Processing in CPU-GPU Hybrid Computing Environments.

Degree: PhD, Computer Science and Engineering, 2015, The Ohio State University

 Massively data-parallel processors, Graphics Processing Units (GPUs) in particular, have recently entered the main stream of general-purpose computing as powerful hardware accelerators to a large… (more)

Subjects/Keywords: Computer Engineering; Computer Science; GPUs, Memory Management, Operating Systems, GPU Databases, Resource Management, Digital Pathology

…Accelerating Pathology Image Data Cross-Comparison on CPU-GPU Hybrid Systems. In Proc. VLDB Endow., 5… …1 Chapter 2 Accelerating Pathology Image Data Cross-Comparison on CPU-GPU Hybrid Systems… …systems. MultiQx-GPU-Raw is a variant of MultiQx-GPU without optimizations. p.q denotes the… …develop resource management facilities in GPU database systems to support efficient concurrent… …systems, device memory space is still managed explicitly by individual applications, which not… 

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APA (6th Edition):

Wang, K. (2015). Algorithmic and Software System Support to Accelerate Data Processing in CPU-GPU Hybrid Computing Environments. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1447685368

Chicago Manual of Style (16th Edition):

Wang, Kaibo. “Algorithmic and Software System Support to Accelerate Data Processing in CPU-GPU Hybrid Computing Environments.” 2015. Doctoral Dissertation, The Ohio State University. Accessed March 04, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1447685368.

MLA Handbook (7th Edition):

Wang, Kaibo. “Algorithmic and Software System Support to Accelerate Data Processing in CPU-GPU Hybrid Computing Environments.” 2015. Web. 04 Mar 2021.

Vancouver:

Wang K. Algorithmic and Software System Support to Accelerate Data Processing in CPU-GPU Hybrid Computing Environments. [Internet] [Doctoral dissertation]. The Ohio State University; 2015. [cited 2021 Mar 04]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1447685368.

Council of Science Editors:

Wang K. Algorithmic and Software System Support to Accelerate Data Processing in CPU-GPU Hybrid Computing Environments. [Doctoral Dissertation]. The Ohio State University; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1447685368

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