Title
Exploration with upgradeable models using statistical methods for physical model emulation
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.
Year
DOI
Venue
2013
10.1145/2463209.2488925
DAC
Keywords
Field
DocType
upgradeable model,single model,fpga area,physical phenomenon,different model,physical model,design space exploration,useful design space,solution space,upgradable model,solution metrics,physical model emulation,statistical method,logic design,internet,statistical analysis,cyber physical systems,fpga,design of experiments,field programmable gate arrays,pareto analysis
Logic synthesis,Computer science,Field-programmable gate array,Electronic engineering,Compiler,Emulation,Pareto analysis,Design space exploration,Speedup,Design of experiments
Conference
ISSN
Citations 
PageRank 
0738-100X
0
0.34
References 
Authors
11
3
Name
Order
Citations
PageRank
Bailey Miller1193.91
Frank Vahid22688218.00
Rilesh Patel362.04