A Comparative Analysis of Networks of Workstations and Massively Parallel Processors for Signal Processing
Language: English
Published by BIBLIOSCHOLAR, 2012
- Softcover
- New
Condition: New
£ 21.51
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KlappentextrnrnThe traditional approach to parallel processing has been to use Massively Parallel Processors (MPPs). An alternative design is commercial-off-the-shelf (COTS) workstations connected to high-speed networks. These networks of workst.
Seller Inventory # 6487987
- Title
- A Comparative Analysis of Networks of Workstations and Massively Parallel Processors for Signal Processing
- Author
- Gindhart, David C.
- Publisher
- BIBLIOSCHOLAR
- Publication year
- 2012
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 1249593158
- ISBN 13
- 9781249593157
The traditional approach to parallel processing has been to use Massively Parallel Processors (MPPs). An alternative design is commercial-off-the-shelf (COTS) workstations connected to high-speed networks. These networks of workstations (NOWs) typically have faster processors, heterogeneous environments, and most importantly, offer a lower per node cost. This thesis compares the performance of MPPs and NOWs for the two-dimensional fast Fourier transform (2-D FFT). Three original, high-performance, portable 2-D FFTs have been implemented: the vector-radix, row-column and pipeline. The performance of these algorithms was measured on the Intel Paragon, IBM SP2 and the AFIT NOW, which consists of 6 Sun Ultra workstations connected via the Myrinet switch. Three important conclusions have been made. First, the pipeline was the best algorithm on all platforms by approximately 30%. Second, the NOW was nearly equal to the SP2 in runtime, while the Paragon did not outperform a single Ultra workstation. As a result, NOWs are a competitive platform for this application. Finally, only limited speedup was achieved on the SP2 (2.9) with 32 processors, and AFIT NOW (1.9) with 5 processors. It appears that the changing platform communication-to-computation ratio has made the 2-D FFT a less viable candidate for parallelization, given its high communication overhead.
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