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Reconfigurable computers: an empirical analysis (abstract only)
Source International Symposium on Field Programmable Gate Arrays archive
Proceedings of the 2005 ACM/SIGDA 13th international symposium on Field-programmable gate arrays table of contents
Monterey, California, USA
POSTER SESSION: Novel applications of reconfigurability table of contents
Pages: 278 - 278  
Year of Publication: 2005
ISBN:1-59593-029-9
Authors
Tarek El-Ghazawi  The George Washington University, Washington DC
Kris Gaj  George Mason University, Fairfax, VA
Nikitas Alexandridis  The George Washington University, Washington DC
Allen Michalski  George Mason University, Fairfax, VA
Devrim Fidanci  The George Washington University, Washington DC
Mohamed Taher  The George Washington University, Washington DC
Esam El-Araby  The George Washington University, Washington DC
Esmail Chitalwala  The George Washington University, Washington DC
Proshanta Saha  The George Washington University, Washington DC
Sponsors
ACM: Association for Computing Machinery
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
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ABSTRACT

Reconfigurable Computers are parallel systems that are designed around multiple general-purpose processors and multiple field programmable gate array (FPGA) chips. These systems can leverage the synergism between conventional processors and FPGAs to provide low-level hardware functionality at the same level of programmability as general-purpose computers. In this work we conduct an experimental study using one of the state-of-the-art reconfigurable computers and a representative set of applications to assess the field, uncover the challenges, propose solutions, and conceive a realistic evolution path. We consider issues of concern including performance/cost. We also consider productivity in the sense of development, compiling, running, and system reliability. It will be shown that for some applications, the performance/cost can be orders of magnitude better than conventional computers. It will be also shown that programming such machines may still require some hardware knowledge, similar to hardware knowledge computer programmers must acquire to write scalable programs.


Collaborative Colleagues:
Tarek El-Ghazawi: colleagues
Kris Gaj: colleagues
Nikitas Alexandridis: colleagues
Allen Michalski: colleagues
Devrim Fidanci: colleagues
Mohamed Taher: colleagues
Esam El-Araby: colleagues
Esmail Chitalwala: colleagues
Proshanta Saha: colleagues