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Content Provider | ACM Digital Library |
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Author | Vahid, Frank Miller, Bailey Givargis, Tony |
Abstract | Physical models capture environmental phenomena such as biochemical reactions, a beating heart, or neuron synapses, using mathematical equations. Previous work has shown that physical models can execute orders of magnitude faster on FPGAs (Field-Programmable Gate Arrays) compared to desktop PCs. Different models of the same physical phenomenon may vary, with "upgraded" models being more accurate but using more FPGA area and having slower performance. We propose that design space exploration considering upgradable models can dramatically increase the useful design space. We present an analysis of the solution space for utilizing networks of processing-elements (PEs) on FPGAs to emulate physical models, implement a web-based frontend to a compiler and cycle-accurate simulator of PE networks to estimate solution metrics, and utilize design-of-experiments (DOE) statistical methods to identify Pareto points. By considering upgradeable models during the design space exploration of a human lung physical model, the solution space of possible speedup, area, and accuracy is increased by 6X, 7.3X, and 1.5X, respectively, compared to evaluating a single model. |
Starting Page | 1 |
Ending Page | 6 |
Page Count | 6 |
File Format | |
ISBN | 9781450320719 |
DOI | 10.1145/2463209.2488925 |
Language | English |
Publisher | Association for Computing Machinery (ACM) |
Publisher Date | 2013-05-29 |
Publisher Place | New York |
Access Restriction | Subscribed |
Subject Keyword | Fpga Cyber-physical systems Design space exploration |
Content Type | Text |
Resource Type | Article |
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