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High-Performance Computing Using FPGAs

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Cover of 'High-Performance Computing Using FPGAs'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 High-Performance Hardware Acceleration of Asset Simulations
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    Chapter 2 Monte-Carlo Simulation-Based Financial Computing on the Maxwell FPGA Parallel Machine
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    Chapter 3 Bioinformatics Applications on the FPGA-Based High-Performance Computer RIVYERA
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    Chapter 4 FPGA-Accelerated Molecular Dynamics
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    Chapter 5 FPGA-Based HPRC for Bioinformatics Applications
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    Chapter 6 High-Performance Computing for Neuroinformatics Using FPGA
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    Chapter 7 High-Performance FPGA-Accelerated Real-Time Search
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    Chapter 8 High-Performance Data Processing Over N -ary Trees
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    Chapter 9 FPGA-Based Systolic Computational-Memory Array for Scalable Stencil Computations
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    Chapter 10 High Performance Implementation of RTM Seismic Modeling on FPGAs: Architecture, Arithmetic and Power Issues
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    Chapter 11 High-Performance Cryptanalysis on RIVYERA and COPACOBANA Computing Systems
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    Chapter 12 FPGA-Based HPRC Systems for Scientific Applications
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    Chapter 13 Accelerating the SPICE Circuit Simulator Using an FPGA: A Case Study
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    Chapter 14 The Convey Hybrid-Core Architecture
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    Chapter 15 Low Cost High Performance Reconfigurable Computing
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    Chapter 16 An FPGA-Based Supercomputer for Statistical Physics: The Weird Case of Janus
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    Chapter 17 Accelerate Communication, not Computation!
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    Chapter 18 High-Speed Torus Interconnect Using FPGAs
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    Chapter 19 MEMSCALE: Re-architecting Memory Resources for Clusters
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    Chapter 20 High-Performance Computing Based on High-Speed Dynamic Reconfiguration
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    Chapter 21 Reconfigurable Arithmetic for High-Performance Computing
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    Chapter 22 Acceleration of the Discrete Element Method: From RTL to C-Based Design
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    Chapter 23 Optimising Euroben Kernels on Maxwell
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    Chapter 24 Assessing Productivity of High-Level Design Methodologies for High-Performance Reconfigurable Computers
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    Chapter 25 Maximum Performance Computing with Dataflow Engines
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    Chapter 26 Erratum: MEMSCALE: Re-architecting Memory Resources for Clusters
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Title
High-Performance Computing Using FPGAs
Published by
Springer-Verlag New York, January 2013
DOI 10.1007/978-1-4614-1791-0
ISBNs
978-1-4614-1790-3, 978-1-4614-1791-0, 978-1-4939-4310-4
Editors

Wim Vanderbauwhede, Khaled Benkrid

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 134 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
Austria 1 <1%
Sweden 1 <1%
Malta 1 <1%
Malaysia 1 <1%
Russia 1 <1%
China 1 <1%
Spain 1 <1%
Poland 1 <1%
Other 0 0%
Unknown 124 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 45 34%
Student > Master 22 16%
Researcher 14 10%
Professor > Associate Professor 13 10%
Student > Bachelor 8 6%
Other 18 13%
Unknown 14 10%
Readers by discipline Count As %
Computer Science 51 38%
Engineering 48 36%
Physics and Astronomy 6 4%
Agricultural and Biological Sciences 5 4%
Economics, Econometrics and Finance 2 1%
Other 8 6%
Unknown 14 10%