- author = "Henry Cook and Kevin Skadron",
- title = "Genetically Programmed Response Surfaces for Efficient Design Space Exploration",
- institution = "Department of Computer Science, University of Virginia",
- year = "2007",
- number = "CS-2007-12",
- address = "USA",
- month = aug,
- keywords = "genetic algorithms, genetic programming",
-
URL = "
https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=74e47f95ea3a0f963dc30ed86835927f8ac8cf4d",
- size = "15 pages",
-
abstract = "In spite of many efforts to speed up cycle-accurate
architecture simulation, exponential increases in
architectural design complexity threaten to make
traditional design optimization techniques completely
intractable. Response surface methodologies address
this challenge by transforming the optimization process
from a lengthy series of detailed simulations into the
tractable formulation and rapid evaluation of a
marginally less accurate but easy to evaluate
analytical expression—a predictive model. We propose
genetic programming as a powerful method for creating
these predictive response surface models out of sampled
architectural performance data.
Genetically programmed response surfaces (GPRSs) allow the architect to make rapid design optimizations (because only a small number of detailed simulations are needed) while simultaneously obtaining insight into the problem domain (because the resulting response surface, a non-linear polynomial in our case, exposes relationships and relative weights among the design variables). We validate our methodology on realistic datasets and compare it to recently proposed techniques for predictive design space exploration. GPRSs are highly accurate when making global predictions about architectural performance behavior based on only small samples of performance data: global predictions of IPC incur less than 3 percent mean percentage error based on sample sizes of less than 1 percent of one target processor design space, and no worse than than mean 6 percent error at sample sizes as small as 0.0000002 percent out of over one billion possible design points from a second target space. GPRSs can therefore reduce required simulation costs by up to six orders of magnitude.",
- notes = "\cite{GPRS-kit}",
