scholarly journals ORION 2.0: A fast and accurate NoC power and area model for early-stage design space exploration

2009 ◽  
Author(s):  
A.B. Kahng ◽  
Bin Li ◽  
Li-Shiuan Peh ◽  
K. Samadi
Keyword(s):  
Design Space Exploration ◽  
Design Space ◽  
Early Stage ◽  
Space Exploration ◽  
Stage Design ◽  
Area Model ◽  
Early Stage Design

scholarly journals Effects of Robust Convex Optimization on Early-Stage Design Space Exploratory Behavior

2020 ◽  
Vol 142 (12) ◽  
Author(s):  
Priya P. Pillai ◽  
Edward Burnell ◽  
Xiqing Wang ◽  
Maria C. Yang
Keyword(s):  
Robust Optimization ◽  
Design Space Exploration ◽  
Design Space ◽  
Early Stage ◽  
Pareto Frontier ◽  
Design Parameters ◽  
Safety Factors ◽  
Worst Case ◽  
Robust Convex Optimization ◽  
Early Stage Design

Abstract Engineers design for an inherently uncertain world. In the early stages of design processes, they commonly account for such uncertainty either by manually choosing a specific worst-case and multiplying uncertain parameters with safety factors or by using Monte Carlo simulations to estimate the probabilistic boundaries in which their design is feasible. The safety factors of this first practice are determined by industry and organizational standards, providing a limited account of uncertainty; the second practice is time intensive, requiring the development of separate testing infrastructure. In theory, robust optimization provides an alternative, allowing set-based conceptualizations of uncertainty to be represented during model development as optimizable design parameters. How these theoretical benefits translate to design practice has not previously been studied. In this work, we analyzed the present use of geometric programs as design models in the aerospace industry to determine the current state-of-the-art, then conducted a human-subjects experiment to investigate how various mathematical representations of uncertainty affect design space exploration. We found that robust optimization led to far more efficient explorations of possible designs with only small differences in an experimental participant’s understanding of their model. Specifically, the Pareto frontier of a typical participant using robust optimization left less performance “on the table” across various levels of risk than the very best frontiers of participants using industry-standard practices.

Design Space Exploration of a 512KB STT-Assisted SOT MRAM Cache

2020 ◽  
Author(s):  
Adrian G. Caburnay ◽  
Jonathan Gabriel S.A. Reyes ◽  
Anastacia P. Ballesil-Alvarez ◽  
Maria Theresa G. de Leon ◽  
John Richard E. Hizon ◽  
...  
Keyword(s):  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration

scholarly journals Optode Design Space Exploration for Clinically-robust Non-invasive Fetal Oximetry

2019 ◽  
Vol 18 (5s) ◽  
pp. 1-22 ◽  
Author(s):  
Daniel D. Fong ◽  
Vivek J. Srinivasan ◽  
Kourosh Vali ◽  
Soheil Ghiasi
Keyword(s):  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Non Invasive
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