Relevant bibliographies by topics / Sparse distributed memory

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Sparse distributed memory'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Sparse distributed memory"

1

Murdock, Bennet. "Sparse distributed memory." Acta Psychologica 76, no. 1 (1991): 92–94. http://dx.doi.org/10.1016/0001-6918(91)90056-6.

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Kang, Mingu, and Naresh R. Shanbhag. "In-Memory Computing Architectures for Sparse Distributed Memory." IEEE Transactions on Biomedical Circuits and Systems 10, no. 4 (2016): 855–63. http://dx.doi.org/10.1109/tbcas.2016.2545402.

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Snaider, Javier, Stan Franklin, Steve Strain, and E. Olusegun George. "Integer sparse distributed memory: Analysis and results." Neural Networks 46 (October 2013): 144–53. http://dx.doi.org/10.1016/j.neunet.2013.05.005.

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Hong, Y. S., and S. S. Chen. "Character recognition in a sparse distributed memory." IEEE Transactions on Systems, Man, and Cybernetics 21, no. 3 (1991): 674–78. http://dx.doi.org/10.1109/21.97459.

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Anwar, Ashraf, and Stan Franklin. "Sparse distributed memory for ‘conscious’ software agents." Cognitive Systems Research 4, no. 4 (2003): 339–54. http://dx.doi.org/10.1016/s1389-0417(03)00015-9.

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Wu, J., R. Das, J. Saltz, H. Berryman, and S. Hiranandan. "Distributed memory compiler design for sparse problems." IEEE Transactions on Computers 44, no. 6 (1995): 737–53. http://dx.doi.org/10.1109/12.391186.

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Snaider, Javier, and Stan Franklin. "Extended Sparse Distributed Memory and Sequence Storage." Cognitive Computation 4, no. 2 (2012): 172–80. http://dx.doi.org/10.1007/s12559-012-9125-8.

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Furber, Steve B., W. John Bainbridge, J. Mike Cumpstey, and Steve Temple. "Sparse distributed memory using N-of-M codes." Neural Networks 17, no. 10 (2004): 1437–51. http://dx.doi.org/10.1016/j.neunet.2004.07.003.

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Silva, Marcus Tadeu Pinheiro, Antônio Pádua Braga, and Wilian Soares Lacerda. "Reconfigurable co-processor for Kanerva's sparse distributed memory." Microprocessors and Microsystems 28, no. 3 (2004): 127–34. http://dx.doi.org/10.1016/j.micpro.2004.01.003.

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Hely, T. A., D. J. Willshaw, and G. M. Hayes. "A new approach to Kanerva's sparse distributed memory." IEEE Transactions on Neural Networks 8, no. 3 (1997): 791–94. http://dx.doi.org/10.1109/72.572115.

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Dissertations / Theses on the topic "Sparse distributed memory"

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Brogliato, Marcelo Salhab. "Understanding the critical distance in sparse distributed memory." reponame:Repositório Institucional do FGV, 2012. http://hdl.handle.net/10438/13095.

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Submitted by Marcelo Salhab Brogliato (msbrogli@gmail.com) on 2015-01-05T20:39:25Z No. of bitstreams: 1 !FullThesis-v6 -biblioteca-digital.pdf: 64255589 bytes, checksum: 0ca16d02e6d615b8fc4c6f4f46db2c22 (MD5)<br>Approved for entry into archive by ÁUREA CORRÊA DA FONSECA CORRÊA DA FONSECA (aurea.fonseca@fgv.br) on 2015-01-06T12:52:32Z (GMT) No. of bitstreams: 1 !FullThesis-v6 -biblioteca-digital.pdf: 64255589 bytes, checksum: 0ca16d02e6d615b8fc4c6f4f46db2c22 (MD5)<br>Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2015-01-12T12:15:58Z (GMT) No. of bitstreams: 1 !Ful
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Sid, Lakhdar Mohamed Wissam. "Scaling the solution of large sparse linear systems using multifrontal methods on hybrid shared-distributed memory architectures." Thesis, Lyon, École normale supérieure, 2014. http://www.theses.fr/2014ENSL0958/document.

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La résolution de systèmes d'équations linéaires creux est au cœur de nombreux domaines d'applications. De même que la quantité de ressources de calcul augmente dans les architectures modernes, offrant ainsi de nouvelles perspectives, la taille des problèmes rencontré de nos jours dans les applications de simulations numériques augmente aussi et de façon significative. L'exploitation des architectures modernes pour la résolution efficace de problèmes de très grande taille devient ainsi un défit a relever, aussi bien d'un point de vue théorique que d'un point de vue algorithmique. L'objectif de
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Hong, Chao, and 洪潮. "Parallel processing in power systems computation on a distributed memory message passing multicomputer." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B3124032X.

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Hong, Chao. "Parallel processing in power systems computation on a distributed memory message passing multicomputer /." Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk/hkuto/record.jsp?B22050383.

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Chada, Daniel de Magalhães. "Are you experienced? Contributions towards experience recognition, cognition, and decision making." reponame:Repositório Institucional do FGV, 2016. http://hdl.handle.net/10438/17786.

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Submitted by Daniel Chada (danielc2112@gmail.com) on 2017-01-10T13:25:02Z No. of bitstreams: 1 chada.phd.2017.01.09.pdf: 5177057 bytes, checksum: a6174d9f2ba0b373776e750def2a23aa (MD5)<br>Approved for entry into archive by ÁUREA CORRÊA DA FONSECA CORRÊA DA FONSECA (aurea.fonseca@fgv.br) on 2017-01-12T14:03:51Z (GMT) No. of bitstreams: 1 chada.phd.2017.01.09.pdf: 5177057 bytes, checksum: a6174d9f2ba0b373776e750def2a23aa (MD5)<br>Made available in DSpace on 2017-01-23T11:48:10Z (GMT). No. of bitstreams: 1 chada.phd.2017.01.09.pdf: 5177057 bytes, checksum: a6174d9f2ba0b373776e750def2a23aa (MD
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Kogeyama, Renato. "Who is the cowboy in Washington?: beating google at their own game with neuroscience and cryptography." reponame:Repositório Institucional do FGV, 2014. http://hdl.handle.net/10438/13524.

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Submitted by RENATO Kogeyama (rkogeyama@gmail.com) on 2015-03-06T14:50:01Z No. of bitstreams: 1 Dissertação final.pdf: 1794273 bytes, checksum: b90c57e65dc2272d6edcdbabe5703b90 (MD5)<br>Approved for entry into archive by Janete de Oliveira Feitosa (janete.feitosa@fgv.br) on 2015-03-10T12:44:03Z (GMT) No. of bitstreams: 1 Dissertação final.pdf: 1794273 bytes, checksum: b90c57e65dc2272d6edcdbabe5703b90 (MD5)<br>Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2015-03-12T19:58:58Z (GMT) No. of bitstreams: 1 Dissertação final.pdf: 1794273 bytes, checksum: b90c57e65dc227
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Aguiar, Matheus Araújo. "Um agente jogador de GO com busca em árvore Monte-Carlo aprimorada por memória esparsamente distribuída." Universidade Federal de Uberlândia, 2013. https://repositorio.ufu.br/handle/123456789/12547.

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The game of Go is very ancient, with more than 4000 years of history and it is still popular nowadays, representing a big challenge to the Articial Intelligence. Despite its simple rules, the techniques which obtained success in other games like chess and draughts cannot handle satisfactorily the complex patterns and behaviours that emerge during a match of Go. The present work implements the SDM-Go, a competitive agent for Go that seeks to reduce the usage of supervision in the search process for the best move. The SDMGo utilizes the sparse distributed memory model as an additional resource t
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Mendes, Mateus Daniel Almeida. "Intelligent robot navigation using a sparse distributed memory." Doctoral thesis, 2010. http://hdl.handle.net/10316/17781.

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Tese de doutoramento em Ciências (Engenharia Electrónica e de Computadores) apresentada à Faculdade de Ciências e Tecnologia da Universidade de Coimbra.<br>The dream of building intelligent machines dates back thousands of years. However, despite the huge advancements in science and technology, modern robots are still fit only to very specific tasks. There are no general-purpose robots able to learn and perform any kind of task the way humans do. Part of the problem arises from the fact that the concept of intelligence is not clearly defined, implying that researchers are pursuing a moving tar
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Chang, Rong-Guey, and 張榮貴. "Compiler Optimizations with Parallel Sparse Computations on Distributed Memory Environments." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/16505492301638850097.

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博士<br>國立清華大學<br>資訊工程學系<br>89<br>Fortran 90 provides a rich set of array intrinsic functions. Each of these array intrinsic functions operates on the elements of multi-dimensional array objects concurrently. They provide a rich source of parallelism and play an increasingly important role in automatic support of data parallel programming. However, there is no such support if these intrinsic functions are applied to sparse data sets. In this dissertation, firstly, we address this open gap by presenting an efficient library for parallel sparse computations with Fortran 90 ar
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Yu, Jen-Chih, and 余仁智. "Efficient Compositing Methods for the Sort-Last-Sparse Parallel Volume Rendering System on Distributed Memory Multicomputers." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/66626452145714623469.

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碩士<br>逢甲大學<br>資訊工程學系<br>87<br>In the sort-last-sparse parallel volume rendering system on distributed memory multicomputers, as the number of processors increases, in the rendering phase, we can get a good speedup because each processor renders images locally without communicating with other processors. However, in the compositing phase, a processor has to exchange local images with other processors. When the number of processors is over a threshold, the image compositing time becomes a bottleneck. In this thesis, we proposed three compositing methods, the binary-swap with bounding rectangl
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Books on the topic "Sparse distributed memory"

1

Kanerva, Pentti. Sparse distributed memory. MIT Press, 1988.

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Flynn, M. J. Sparse distributed memory principles of operation. Research Institute for Advanced Computer Science, 1989.

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Kanerva, Pentti. Sparse distributed memory and related models. Research Institute for Advanced Computer Science, NASA Ames Research Center, 1992.

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Denning, Peter J. Sparse disributed memory. Research Institute for Advanced Computer Science, [NASA Ames Research Center, 1989.

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Denning, Peter J. A view of Kanerva's sparse distributed memory. Research Institute for Advanced Computer Science, NASA Ames Research Center, 1986.

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Rogers, David. Statistical prediction with Kanerva's sparse distributed memory. Research Institute for Advanced Computer Science, 1989.

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Sun, Chunguang. Parallel sparse orthogonal factorization on distributed-memory multiprocessors. Cornell Theory Center, Cornell University, 1993.

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Amestoy, P. R. Performance and tuning of two distributed memory sparse solvers. Rutherford Appleton Laboratory, 2001.

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Rogers, David. BIRD: A general interface for sparse distributed memory simulators. Research Institute for Advanced Computer Science, NASA Ames Research Center, 1990.

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L, Brown Robert. Two demonstrators and a simulator for a sparse, distributed memory. Research Institute for Advanced Computer Science, NASA Ames Research Center, 1987.

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Book chapters on the topic "Sparse distributed memory"

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Eswar, Kalluri, P. Sadayappan, and V. Visvanathan. "Parallel Direct Solution of Sparse Linear Systems." In Parallel Computing on Distributed Memory Multiprocessors. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-58066-6_6.

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Ercal, Fikret, Neil L. Book, and Sinar Pait. "Sparse LU-Decomposition for Chemical Process Flowsheeting on a Multicomputer." In Parallel Computing on Distributed Memory Multiprocessors. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-58066-6_8.

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Liu, Yang, Mathias Jacquelin, Pieter Ghysels, and Xiaoye S. Li. "Highly scalable distributed-memory sparse triangular solution algorithms." In 2018 Proceedings of the Seventh SIAM Workshop on Combinatorial Scientific Computing. Society for Industrial and Applied Mathematics, 2018. http://dx.doi.org/10.1137/1.9781611975215.9.

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Amestoy, Patrick R., Iain S. Duff, Jean-Yves L’Excellent, and Jacko Koster. "MUMPS: A General Purpose Distributed Memory Sparse Solver." In Applied Parallel Computing. New Paradigms for HPC in Industry and Academia. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-70734-4_16.

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Wang, Xiaowei, and Hongying Meng. "Integer Sparse Distributed Memory Based on Neural Coding." In Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70665-4_107.

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Mendes, Mateus, A. Paulo Coimbra, Manuel M. Crisóstomo, and Jorge Rodrigues. "Experiments with a Sparse Distributed Memory for Text Classification." In Transactions on Engineering Technologies. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-8832-8_40.

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Kolinummi, Pasi, Timo Hämäläinen, and Jukka Saarinen. "Sparse Distributed Memory Mapping on Partial Tree Shape Neurocomputer." In ICANN 98. Springer London, 1998. http://dx.doi.org/10.1007/978-1-4471-1599-1_69.

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Mendes, Mateus, Manuel M. Crisóstomo, and A. Paulo Coimbra. "Encoding Data to Use with a Sparse Distributed Memory." In Lecture Notes in Electrical Engineering. Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-8776-8_25.

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Mendes, Mateus, A. Paulo Coimbra, and Manuel M. Crisóstomo. "Topological Mapping Using Vision and a Sparse Distributed Memory." In Electrical Engineering and Applied Computing. Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-1192-1_23.

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Gupta, Anshul. "A Shared- and Distributed-Memory Parallel Sparse Direct Solver." In Applied Parallel Computing. State of the Art in Scientific Computing. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11558958_94.

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Conference papers on the topic "Sparse distributed memory"

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Mendes, Mateus, Manuel Crisostomo, and A. Paulo Coimbra. "Robot navigation using a sparse distributed memory." In 2008 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2008. http://dx.doi.org/10.1109/robot.2008.4543186.

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Jockel, S., F. Lindner, and Jianwei Zhang. "Sparse distributed memory for experience-based robot manipulation." In 2008 IEEE International Conference on Robotics and Biomimetics. IEEE, 2009. http://dx.doi.org/10.1109/robio.2009.4913187.

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Eswar, Kalluri, P. Sadayappan, Chua-Huang Huang, and V. Visvanathan. "Supernodal Sparse Cholesky Factorization on Distributed-Memory Multiprocessors." In 1993 International Conference on Parallel Processing - ICPP'93 Vol3. IEEE, 1993. http://dx.doi.org/10.1109/icpp.1993.170.

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Kaya, Oguz, and Bora Uçar. "Scalable sparse tensor decompositions in distributed memory systems." In SC15: The International Conference for High Performance Computing, Networking, Storage and Analysis. ACM, 2015. http://dx.doi.org/10.1145/2807591.2807624.

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Malkowski, Konrad, Padma Raghavan, and Mary Jane Irwin. "Memory Optimizations For Fast Power-Aware Sparse Computations." In 2007 IEEE International Parallel and Distributed Processing Symposium. IEEE, 2007. http://dx.doi.org/10.1109/ipdps.2007.370501.

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Kim, Kyungjoo, H. Carter Edwards, and Sivasankaran Rajamanickam. "Tacho: Memory-Scalable Task Parallel Sparse Cholesky Factorization." In 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). IEEE, 2018. http://dx.doi.org/10.1109/ipdpsw.2018.00094.

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Kang, Mingu, Eric P. Kim, Min-sun Keel, and Naresh R. Shanbhag. "Energy-efficient and high throughput sparse distributed memory architecture." In 2015 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2015. http://dx.doi.org/10.1109/iscas.2015.7169194.

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Boudreau, Luke, and Dhireesha Kudithipudi. "Binding of Sparse Distributed Representations in Hierarchical Temporal Memory." In the 7th Annual Neuro-inspired Computational Elements Workshop. ACM Press, 2019. http://dx.doi.org/10.1145/3320288.3320299.

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Anderson. "A conditional probability interpretation of Kanerva's sparse distributed memory." In International Joint Conference on Neural Networks. IEEE, 1989. http://dx.doi.org/10.1109/ijcnn.1989.118597.

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Kapre, Nachiket, Han Jianglei, Andrew Bean, Pradeep Moorthy, and Siddhartha. "GraphMMU: Memory Management Unit for Sparse Graph Accelerators." In 2015 IEEE 29th International Parallel and Distributed Processing Symposium Workshop (IPDPSW). IEEE, 2015. http://dx.doi.org/10.1109/ipdpsw.2015.101.

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Reports on the topic "Sparse distributed memory"

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Devine, Karen, and Grey Ballard. GentenMPI: Distributed Memory Sparse Tensor Decomposition. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1656940.

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Pothen, A. Sparse matrix algorithms on distributed memory multiprocessors. Office of Scientific and Technical Information (OSTI), 1992. http://dx.doi.org/10.2172/7205554.

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Pothen, A. Sparse matrix algorithms on distributed memory multiprocessors. Office of Scientific and Technical Information (OSTI), 1993. http://dx.doi.org/10.2172/6645453.

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Pothen, A. Sparse matrix algorithms on distributed memory multiprocessors. Progress report, June 1991--January 1992. Office of Scientific and Technical Information (OSTI), 1992. http://dx.doi.org/10.2172/10161122.

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Amestoy, P. R., I. S. Duff, J. Y. L'Excellent, and X. S. Li. Analysis, tuning and comparison of two general sparse solvers for distributed memory computers. Office of Scientific and Technical Information (OSTI), 2000. http://dx.doi.org/10.2172/776597.

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Pothen, A. Sparse matrix algorithms on distributed memory multiprocessors. Progress report, June 1992--February 1993. Office of Scientific and Technical Information (OSTI), 1993. http://dx.doi.org/10.2172/10131173.

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