Predicting Conversion Time of Circuit Design File by Artificial Neural Networks
2008
GDSII is a data format of the circuit design file for producing semiconductor. GDSII is also used as a transfer format for
fabricating photo mask as well. As design rules are getting smaller and RET (Resolution Enhancement Technology) is
getting more complicated, the time of converting GDSII to a mask data format has been increased, which influences the
period of mask production. Photo mask shops all over the world are widely using computer clusters which are connected
through a network, that is, called distributed computing method, to reduce the converting time. Commonly computing
resource for conversion is assigned based on the input file size. However, the result of experiments showed that the
input file size was improper to predict the computing resource usage. In this paper, we propose the methodology of
artificial intelligence with considering the properties of GDSII file to handle circuit design files more efficiently. The
conversion time will be optimized by controlling the hardware resource for data conversion as long as the conversion
time is predictable through analyzing the design data. Neural networks are used to predict the conversion time for this
research. In this paper, the application of neural networks for the time prediction will be discussed and experimental
results will be shown with comparing to statistical model based approaches.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
0
References
0
Citations
NaN
KQI