Parallel computing: technology trends
Advances in parallel computing ;, v. 36./ edited by Ian Foster (Argonne National Laboratory and University of Chicago, Chicago, USA), Gerhard R. Joubert (Technical University Clausthal, Clausthal-Zellerfeld, Germany), Luděk Kučera (Charles University, Prague, Czech Republic), Wolfgang E. Nagel (Technical University Dresden, Dresden, Germany) and Frans Peters (formerly Philips Research, Eindhoven, Netherlands).

Foster Ian; Nagel Wolfgang E.,; Joubert G. R.; Peters F. J.,; Kučera Luděk

Parallel computing: technology trends Advances in parallel computing ;, v. 36./ edited by Ian Foster (Argonne National Laboratory and University of Chicago, Chicago, USA), Gerhard R. Joubert (Technical University Clausthal, Clausthal-Zellerfeld, Germany), Luděk Kučera (Charles University, Prague, Czech Republic), Wolfgang E. Nagel (Technical University Dresden, Dresden, Germany) and Frans Peters (formerly Philips Research, Eindhoven, Netherlands).

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dc.contributor.author	Foster Ian
dc.contributor.author	Joubert G. R.
dc.contributor.author	Kučera Luděk
dc.contributor.author	Nagel Wolfgang E.,
dc.contributor.author	Peters F. J.,
dc.date.accessioned	2024-01-29T21:47:13Z
dc.date.available	2024-01-29T21:47:13Z
dc.date.issued	2020
dc.identifier.citation	Parallel computing: technology trends Advances in parallel computing ;, v. 36. - 1 online resource (xvii, 785 pages) - URL: https://libweb.kpfu.ru/ebsco/pdf/2512603.pdf
dc.identifier.isbn	9781643680712
dc.identifier.isbn	1643680714
dc.identifier.issn	0927-5452 ;
dc.identifier.uri	https://dspace.kpfu.ru/xmlui/handle/net/179913
dc.description	Conference: "ParCo2019, held in Prague, Czech Republic, from 10-13 September 2019, ..."--Back cover.
dc.description	Includes bibliographical references and indexes.
dc.description.tableofcontents	Intro -- Title Page -- Preface -- Conference Organisation -- Contents -- Opening -- Four Decades of Cluster Computing -- Invited Talks -- Will We Ever Have a Quantum Computer? -- Empowering Parallel Computing with Field Programmable Gate Arrays -- Main Track -- Deep Learning Applications -- First Experiences on Applying Deep Learning Techniques to Prostate Cancer Detection -- Deep Generative Model Driven Protein Folding Simulations -- Economics -- A Scalable Approach to Econometric Inference -- Cloud vs On-Premise HPC: A Model for Comprehensive Cost Assessment -- GPU Computing Methods
dc.description.tableofcontents	GPU Architecture for Wavelet-Based Video Coding Acceleration -- GPGPU Computing for Microscopic Pedestrian Simulation -- High Performance Eigenvalue Solver for Hubbard Model: Tuning Strategies for LOBPCG Method on CUDA GPU -- Parallel Smoothers in Multigrid Method for Heterogeneous CPU-GPU Environment -- Load Balancing Methods -- Progressive Load Balancing in Distributed Memory. Mitigating Performance and Progress Variability in Iterative Asynchronous Algorithms -- Learning-Based Load Balancing for Massively Parallel Simulations of Hot Fusion Plasmas
dc.description.tableofcontents	Load-Balancing for Large-Scale Soot Particle Agglomeration Simulations -- On the Autotuning of Task-Based Numerical Libraries for Heterogeneous Architectures -- Parallel Algorithms -- Batched 3D-Distributed FFT Kernels Towards Practical DNS Codes -- On Superlinear Speedups of a Parallel NFA Induction Algorithm -- A Domain Decomposition Reduced Order Model with Data Assimilation (DD-RODA) -- Predicting Performance of Classical and Modified BiCGStab Iterative Methods -- Parallel Applications -- Gadget3 on GPUs with OpenACC -- Exploring High Bandwidth Memory for PET Image Reconstruction
dc.description.tableofcontents	Parallel Architecture -- The Architecture of Heterogeneous Petascale HPC RIVR -- Design of an FPGA-Based Matrix Multiplier with Task Parallelism -- Application Performance of Physical System Simulations -- Parallel Methods -- A Hybrid MPI+Threads Approach to Particle Group Finding Using Union-Find -- Parallel Performance -- Improving the Scalability of the ABCD Solver with a Combination of New Load Balancing and Communication Minimization Techniques -- Characterization of Power Usage and Performance in Data-Intensive Applications Using MapReduce over MPI
dc.description.tableofcontents	Feedback-Driven Performance and Precision Tuning for Automatic Fixed Point Exploitation -- Parallel Programming -- A GPU-CUDA Framework for Solving a Two-Dimensional Inverse Anomalous Diffusion Problem -- Parallelization Strategies for GPU-Based Ant Colony Optimization Applied to TSP -- DBCSR: A Blocked Sparse Tensor Algebra Library -- Acceleration of Hydro Poro-Elastic Damage Simulation in a Shared-Memory Environment -- BERTHA and PyBERTHA: State of the Art for Full Four-Component Dirac-Kohn-Sham Calculations -- Prediction-Based Partitions Evaluation Algorithm for Resource Allocation
dc.language	English
dc.language.iso	en
dc.relation.ispartofseries	Advances in parallel computing. v. 36
dc.relation.ispartofseries	Advances in parallel computing ;. v. 36.
dc.subject.other	Parallel processing (Electronic computers) -- Congresses.
dc.subject.other	Parallel processing (Electronic computers)
dc.subject.other	Electronic books.
dc.subject.other	Electronic books.
dc.title	Parallel computing: technology trends Advances in parallel computing ;, v. 36./ edited by Ian Foster (Argonne National Laboratory and University of Chicago, Chicago, USA), Gerhard R. Joubert (Technical University Clausthal, Clausthal-Zellerfeld, Germany), Luděk Kučera (Charles University, Prague, Czech Republic), Wolfgang E. Nagel (Technical University Dresden, Dresden, Germany) and Frans Peters (formerly Philips Research, Eindhoven, Netherlands).
dc.type	Book
dc.contributor.org	ParCo2019
dc.description.pages	1 online resource (xvii, 785 pages)
dc.collection	Электронно-библиотечные системы
dc.source.id	EN05CEBSCO05C584