Suchergebnisse - Computing methodologies → Massively parallel algorithms
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Autoren: et al.
Weitere Verfasser: et al.
Quelle: Proceedings of the 38th ACM International Conference on Supercomputing. :286-297
Schlagwörter: [INFO.INFO-CC]Computer Science [cs]/Computational Complexity [cs.CC], [INFO.INFO-DC]Computer Science [cs]/Distributed, Information extraction, Natural language processing, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], Parallel, Distributed computing, Sparse matrix, Computing methodologies → Massively parallel algorithms, and Cluster Computing [cs.DC], Large-scale data analytics, Control methods Deep Learning, [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], [INFO.INFO-CC] Computer Science [cs]/Computational Complexity [cs.CC], Co-occurrence matrix, Computing methodologies → Massively parallel algorithms Natural language processing Information extraction Control methods Deep Learning, Embedding
Dateibeschreibung: application/pdf
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Autoren: et al.
Quelle: Computer Graphics Forum. Jun2025, Vol. 44 Issue 3, p1-12. 12p.
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Autoren: et al.
Weitere Verfasser: et al.
Schlagwörter: Computing methodologies → Massively parallel algorithms, 0301 basic medicine, 03 medical and health sciences, CCS Concepts, Massively parallel algorithms, 0202 electrical engineering, electronic engineering, information engineering, Applied computing, Molecular structural biology, 02 engineering and technology, Applied computing → Molecular structural biology, [INFO] Computer Science [cs], Computing methodologies
Dateibeschreibung: application/pdf
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Quelle: Vision, Modeling and Visualization
Schlagwörter: Parallel programming languages, Massively parallel algorithms, Computations on matrices, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 0101 mathematics, 01 natural sciences, Mathematics of computing, Computing methodologies
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Autoren: et al.
Index Begriffe: Àrees temàtiques de la UPC::Informàtica, Parallel algorithms, Computational methods in engineering, Mathematics of computing, Computations on matrices, Theory of computation, Numeric approximation algorithms, Massively parallel algorithms, Distributed algorithms, Computing methodologies, Applied computing, Algorismes paral·lels, Supercomputadors, Conference lecture
URL:
http://hdl.handle.net/2117/120202 https://dl.acm.org/citation.cfm?id=3218231 https://dl.acm.org/citation.cfm?id=3218231
info:eu-repo/grantAgreement/EC/H2020/716142/EU/Unravelling the Nature of Green Organic “On-Water” Catalysis via Novel Quantum Chemical Methods/GreenOnWaterCat -
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Autoren: et al.
Quelle: ACM Computing Surveys; Jul2021, Vol. 53 Issue 4, p90-90:38, 38p
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Autoren: et al.
Quelle: ACM transactions on parallel computing [ACM Trans Parallel Comput] 2025 Mar; Vol. 12 (1). Date of Electronic Publication: 2025 Feb 11.
Publikationsart: Journal Article
Info zur Zeitschrift: Publisher: Association for Computing Machinery, Inc NLM ID: 9918937930806676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2329-4957 (Electronic) Linking ISSN: 23294949 NLM ISO Abbreviation: ACM Trans Parallel Comput Subsets: PubMed not MEDLINE
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Quelle: Computer Graphics Forum. Dec2021, Vol. 40 Issue 8, p57-70. 14p. 1 Color Photograph, 2 Black and White Photographs, 3 Charts, 4 Graphs.
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Autoren: et al.
Quelle: Water (20734441); Aug2023, Vol. 15 Issue 15, p2810, 22p
Schlagwörter: HYDROLOGIC models, PARALLEL programming, COMPUTER workstation clusters, PROGRAMMING languages, COMPUTER systems, C++, SENSITIVITY analysis
Firma/Körperschaft: INTEL Corp., NVIDIA Corp.
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Autoren: et al.
Weitere Verfasser: et al.
Schlagwörter: Microscopy, Computing Methodologies → Massively Parallel Algorithms, Parallel Programming Languages, Software And Its Engineering → Development Frameworks And Environments, Integrated And Visual Development Environments, Interactive Visualization And Analysis, Algorithms Scalability, Parallel Custom Analysis Work-flows
Relation: Petruzza, S., Venkat, A., Gyulassy, A., Scorzelli, G., Federer, F., Angelucci, A., … Bremer, P.-T. (2017). ISAVS. SIGGRAPH Asia 2017 Symposium on Visualization. doi:10.1145/3139295.3139299; 2-s2.0-85040047900; PMC6105268; http://hdl.handle.net/10754/679392
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Weitere Verfasser: Young, D
Quelle: Other Information: PBD: Apr 1992
Dateibeschreibung: Medium: ED; Size: 8 p.
Zugangs-URL: http://www.osti.gov/scitech/servlets/purl/10148128
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Autoren: et al.
Schlagwörter: Massively parallel algorithms, Graphics processors, Applied computing, Molecular structural biology, 7. Clean energy, Computing methodologies
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Autoren: et al.
Quelle: Water (20734441); Sep2024, Vol. 16 Issue 18, p2642, 17p
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Quelle: Proceedings of the 2025 International Conference on High Performance Computing in Asia-Pacific Region Workshops. :58-60
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Autoren: et al.
Schlagwörter: ddc:004, strings, Theory of computation → Sorting and searching, Theory of computation → Massively parallel algorithms, Computing methodologies → Distributed algorithms, DATA processing & computer science, Theory of computation → Bloom filters and hashing, distributed membership filters, distributed-memory computing, sorting, scalability
Dateibeschreibung: application/pdf
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Autoren: et al.
Weitere Verfasser: et al.
Quelle: Recercat. Dipósit de la Recerca de Catalunya
instname
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Communications in Computational Physics
Proceedings of the Platform for Advanced Scientific Computing Conference on-PASC '18
Proceedings of the Platform for Advanced Scientific Computing ConferenceSchlagwörter: FOS: Computer and information sciences, Parallel algorithms, Computations on matrices, Mathematics of computing, 01 natural sciences, Computing methodologies, Supercomputadors, Informàtica [Àrees temàtiques de la UPC], Massively parallel algorithms, FOS: Mathematics, Mathematics - Numerical Analysis, 0101 mathematics, Theory of computation, Numeric approximation algorithms, Applied computing, Mathematics - Rings and Algebras, Numerical Analysis (math.NA), Algorismes paral·lels, Computer Science - Distributed, Parallel, and Cluster Computing, Rings and Algebras (math.RA), Distributed algorithms, Computer Science - Mathematical Software, Distributed, Parallel, and Cluster Computing (cs.DC), Àrees temàtiques de la UPC::Informàtica, Computational methods in engineering, Mathematical Software (cs.MS)
Dateibeschreibung: application/pdf
Zugangs-URL: http://arxiv.org/pdf/1703.02456
https://upcommons.upc.edu/bitstream/2117/120202/1/A%20Massively%20Parallel%20Algorithm%20for%20the%20Approximate%20Calculation.pdf
http://arxiv.org/abs/1703.02456
http://arxiv.org/abs/1710.10899
http://hdl.handle.net/2117/120202
http://export.arxiv.org/pdf/1710.10899
https://arxiv.org/pdf/1710.10899
https://arxiv.org/abs/1710.10899
https://ui.adsabs.harvard.edu/abs/2017arXiv171010899L/abstract
https://ui.adsabs.harvard.edu/abs/2017arXiv170302456R/abstract
https://arxiv.org/pdf/1703.02456.pdf
https://www.arxiv.org/abs/1703.02456
https://hdl.handle.net/2117/120202
https://doi.org/10.1145/3218176.3218231 -
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Autoren:
Schlagwörter: Scientific visualization, Realtime simulation, 13. Climate action, Massively parallel algorithms, Massively parallel and high, Human centered computing, Geographic visualization, performance simulations, CCS Concepts: Human-centered computing --> Scientific visualization, Computing methodologies --> Realtime simulation, Massively parallel and high-performance simulations, Computing methodologies
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Autoren: et al.
Quelle: Bioinformatics. 34(12)
Schlagwörter: Biological Sciences, Bioinformatics and Computational Biology, Genetics, Mathematical Sciences, Statistics, Cancer, Human Genome, Biotechnology, Aetiology, 2.5 Research design and methodologies (aetiology), 2.1 Biological and endogenous factors, Good Health and Well Being, Algorithms, DNA Copy Number Variations, Genomics, High-Throughput Nucleotide Sequencing, Humans, Models, Genetic, Models, Statistical, Neoplasms, Polymorphism, Single Nucleotide, Sequence Analysis, DNA, Software, Information and Computing Sciences, Bioinformatics, Biological sciences, Information and computing sciences, Mathematical sciences
Dateibeschreibung: application/pdf
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Autoren: et al.
Weitere Verfasser: et al.
Quelle: Astronomy and Computing. 30:100340
Schlagwörter: Cosmology and Nongalactic Astrophysics (astro-ph.CO), Gravitational lensing, FOS: Physical sciences, Galaxies: halos, 7. Clean energy, 01 natural sciences, Applied computing: Physical sciences and engineering: Astronomy, [PHYS.PHYS.PHYS-INS-DET] Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], 0103 physical sciences, Dark matter, Computing methodologies: Parallel computing methodologies: Parallel algorithms: Massively parallel algorithms, Galaxies: clusters: general, [PHYS.ASTR] Physics [physics]/Astrophysics [astro-ph], Astrophysics - Instrumentation and Methods for Astrophysics, Instrumentation and Methods for Astrophysics (astro-ph.IM), Astrophysics - Cosmology and Nongalactic Astrophysics
Zugangs-URL: http://arxiv.org/pdf/1902.03252
http://arxiv.org/abs/1902.03252
https://www.sciencedirect.com/science/article/pii/S2213133719300137
https://dblp.uni-trier.de/db/journals/ascom/ascom30.html#RexrothSFK20
https://ui.adsabs.harvard.edu/abs/2020A&C....3000340R/abstract
https://hal.science/hal-02051538v1
https://doi.org/10.1016/j.ascom.2019.100340
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