Advanced search
1 file | 97.42 KB

ParaFPGA : parallel computing with flexible hardware

Author
Organization
Abstract
ParaFPGA 2009 is a Mini-Symposium on parallel computing with field programmable gate arrays (FPGAs), held in conjunction with the ParCo conference on parallel computing. FPGAs allow to map an algorithm directly onto the hardware, optimize the architecture for parallel execution, and dynamically reconfigure the system in between different phases of the computation. Compared to e.g. Cell processors, GPGPU's (general-purpose GPU's) and other high-performance devices, FPGAs are considered as flexible hardware in the sense that the building blocks of one or more single or multiple FPGAs can be interconnected freely to build a highly parallel system. In this Mini-Symposium the following topics are addressed: clustering FPGAs, evolvable hardware using FPGAs and fast dynamic reconfiguration.
Keywords
parallel processing, FPGAs, high performance computing, dynamic reconfiguration, flexible hardware

Downloads

  • ParaFPGA - Parallel Computing with Flexible Hardware.pdf
    • full text
    • |
    • open access
    • |
    • PDF
    • |
    • 97.42 KB

Citation

Please use this url to cite or link to this publication:

Chicago
D’Hollander, Erik, Dirk Stroobandt, and Abdellah Touhafi. 2010. “ParaFPGA : Parallel Computing with Flexible Hardware.” In PARALLEL COMPUTING: FROM MULTICORES AND GPU’S TO PETASCALE, ed. Barbara Chapman, Frédéric Desprez, Gerhard R Joubert, Alain Lichnewsky, Frans Peters, and Thierry Priol, 19:581–583. IOS press, Inc.
APA
D’Hollander, E., Stroobandt, D., & Touhafi, A. (2010). ParaFPGA : parallel computing with flexible hardware. In B. Chapman, F. Desprez, G. R. Joubert, A. Lichnewsky, F. Peters, & T. Priol (Eds.), PARALLEL COMPUTING: FROM MULTICORES AND GPU’S TO PETASCALE (Vol. 19, pp. 581–583). Presented at the International Parallel Computing Conference (ParCo) , IOS press, Inc.
Vancouver
1.
D’Hollander E, Stroobandt D, Touhafi A. ParaFPGA : parallel computing with flexible hardware. In: Chapman B, Desprez F, Joubert GR, Lichnewsky A, Peters F, Priol T, editors. PARALLEL COMPUTING: FROM MULTICORES AND GPU’S TO PETASCALE. IOS press, Inc.; 2010. p. 581–3.
MLA
D’Hollander, Erik, Dirk Stroobandt, and Abdellah Touhafi. “ParaFPGA : Parallel Computing with Flexible Hardware.” PARALLEL COMPUTING: FROM MULTICORES AND GPU’S TO PETASCALE. Ed. Barbara Chapman et al. Vol. 19. IOS press, Inc., 2010. 581–583. Print.
@inproceedings{1856521,
  abstract     = {ParaFPGA 2009 is a Mini-Symposium on parallel computing with field programmable gate arrays (FPGAs), held in conjunction with the ParCo conference on parallel computing. FPGAs allow to map an algorithm directly onto the hardware, optimize the architecture for parallel execution, and dynamically reconfigure the system in between different phases of the computation. Compared to e.g. Cell processors, GPGPU's (general-purpose GPU's) and other high-performance devices, FPGAs are considered as flexible hardware in the sense that the building blocks of one or more single or multiple FPGAs can be interconnected freely to build a highly parallel system. In this Mini-Symposium the following topics are addressed: clustering FPGAs, evolvable hardware using FPGAs and fast dynamic reconfiguration.},
  author       = {D'Hollander, Erik and Stroobandt, Dirk and Touhafi, Abdellah},
  booktitle    = {PARALLEL COMPUTING: FROM MULTICORES AND GPU'S TO PETASCALE},
  editor       = {Chapman, Barbara and Desprez, Fr{\'e}d{\'e}ric  and Joubert, Gerhard R and Lichnewsky, Alain  and Peters, Frans  and Priol, Thierry },
  isbn         = {9781607505297},
  issn         = {0927-5452},
  keyword      = {parallel processing,FPGAs,high performance computing,dynamic reconfiguration,flexible hardware},
  language     = {eng},
  location     = {Lyon, France},
  pages        = {581--583},
  publisher    = {IOS press, Inc.},
  title        = {ParaFPGA : parallel computing with flexible hardware},
  url          = {http://dx.doi.org/10.3233/978-1-60750-530-3-581},
  volume       = {19},
  year         = {2010},
}

Altmetric
View in Altmetric
Web of Science
Times cited: