Concurrent multi-mode timing model generation for hierarchical timing analysis

2016 ◽  
Author(s):  
Naresh Kumar ◽  
Parag Bhatnagar ◽  
N. K. Agarwal ◽  
P. S. Bhatnagar
Keyword(s):  
Timing Analysis ◽  
Model Generation ◽  
Timing Model ◽  
Hierarchical Timing ◽  
Multi Mode

scholarly journals Timing Model Reduction for Hierarchical Timing Analysis

2006 ◽  
Author(s):  
Shuo Zhou ◽  
Yi Zhu ◽  
Yuanfang Hu ◽  
Ronald Graham ◽  
Mike Hutton ◽  
...  
Keyword(s):  
Model Reduction ◽  
Timing Analysis ◽  
Timing Model ◽  
Hierarchical Timing

scholarly journals Timing model reduction for hierarchical timing analysis

2006 ◽  
Author(s):  
Shuo Zhou ◽  
Yi Zhu ◽  
Yuanfang Hu ◽  
Ronald Graham ◽  
Mike Hutton ◽  
...  
Keyword(s):  
Model Reduction ◽  
Timing Analysis ◽  
Timing Model ◽  
Hierarchical Timing

Interval Timing in Spoken Lists of Words

2005 ◽  
Vol 22 (3) ◽  
pp. 497-508
Author(s):  
Fred Cummins
Keyword(s):  
Hierarchical Control ◽  
Interval Timing ◽  
Motor Responses ◽  
Timing Model ◽  
S Model ◽  
Interval Production ◽  
Hierarchical Timing

Isochronous interval production with discrete motor responses has been studied most intensively by using well-practiced tapping in a synchronization/continuation paradigm. Somewhat fewer studies have examined the timing of shorter sequences of intervals that may be susceptible to metrical grouping. I here look at the attempted isochronous production of lists of eight trochees and examine the resulting interval patterns both in terms of the Wing-Kristofferson model (A. M. Wing & A. B. Kristofferson, 1973) and Rosenbaum�s hierarchical timing model (D. A. Rosenbaum, S. B. Kenny, & M. A. Derr, 1983). In Experiment 1, readings are self- paced and done under conditions of uncertainty. The Wing-Kristofferson model is not applicable to the data, which more closely resemble data exhibiting hierarchical control of intervals. In Experiment 2, readings are paced, well-practiced, and done without uncertainty. Neither Wing and Kristofferson�s model nor Rosenbaum�s model adequately captures the serial dependencies observed, although under these conditions variability is greatly reduced. In both experiments, there are dependencies between nonadjacent intervals that neither model can yet account for.

ACCURATE GATE DELAY EXTRACTION FOR TIMING ANALYSIS OF BODY-BIASED CIRCUITS

2013 ◽  
Vol 22 (08) ◽  
pp. 1350072 ◽  
Author(s):  
DONKYU BAEK ◽  
INSUP SHIN ◽  
YOUNGSOO SHIN
Keyword(s):  
Bias Voltage ◽  
Timing Analysis ◽  
Average Error ◽  
Gate Delay ◽  
Timing Model ◽  
New Process ◽  
Delay Extraction ◽  
Circuit Technique ◽  
Static Body ◽  
Body Bias

Static body biasing is a circuit technique in which bias voltage is selected from more than one available voltage after manufacturing. It allows circuits to be designed at more favorable process corners; but effective application requires gate delays to be available for the new process corners, without the expense of re-characterizing individual gates. We show that the new delay of a gate (when body bias is applied) can be extrapolated from its old delay without body bias together with old and new delays of a few reference gates. Output transition time, which is another component of gate timing model, is extrapolated in a similar manner. Experiments with an industrial 32-nm gate library show that the average error in the new gate delays is less than 4.3%.

Logic depth aware context independent timing model generation

2016 ◽  
Author(s):  
Parag Bhatnagar ◽  
Naresh Kumar ◽  
P. S. Bhatnagar ◽  
N. K. Agarwal
Keyword(s):  
Model Generation ◽  
Timing Model

Automated timing model generation

2002 ◽  
Author(s):  
Ajay J. Daga ◽  
Loa Mize ◽  
Subramanyam Sripada ◽  
Chris Wolff ◽  
Qiuyang Wu
Keyword(s):  
Model Generation ◽  
Timing Model
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