Data learning techniques and methodology for Fmax prediction
The question of whether or not structural test measurements can be used to predict functional or system Fmax, has been studied for many years. This paper presents a data learning approach to study the question. Given Fmax values and structural delay measurements on a set of sample chips, we propose...
Saved in:
Published in | 2009 International Test Conference pp. 1 - 10 |
---|---|
Main Authors | , , , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.11.2009
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | The question of whether or not structural test measurements can be used to predict functional or system Fmax, has been studied for many years. This paper presents a data learning approach to study the question. Given Fmax values and structural delay measurements on a set of sample chips, we propose a method called conformity check whose goal is to select a subset of conformal samples such that a more reliable predictor can be built on. Our predictor consists of two models, a conformal model that decides on a given chip if its Fmax is predictable or not, and a prediction model that outputs the predicted Fmax based on results obtained from structural test measurements. We explain the data learning methodology and study various data learning techniques using frequency data collected on a high-performance microprocessor design. |
---|---|
ISBN: | 1424448689 9781424448685 |
ISSN: | 1089-3539 2378-2250 |
DOI: | 10.1109/TEST.2009.5355620 |