Large 3DIC designs with multiple chips require
several iterations of transient thermal analysis particularly for
fine-grain on-chip dynamic thermal management. This requires
a fast thermal analysis technology as opposed to traditional
CFD/FEA based methods which have severe runtime/capacity
limitations for large chips (e.g., 2cmx2cm) in 3DIC while
generating fine grained (e.g., 10umx10um) transient thermal
response. The fast transient thermal analysis is based on the idea
of combining the global, intermediate, and local transient
response curves generated from an ML-predictor. The local,
intermediate, and global transient response curves are scaled
based on the far-field and near-field transient decay surface
components respectively, computed using the trained ML decay
surface predictor, followed by linear superposition of the curves
for each power value in the transient power profile to generate
the effective transient response curve. The runtime for
generating thermal results for a large chip is in the order of
minutes, compared to several hours/days while using CFD/FEA
based tools with good accuracy correlation. The fast transient
thermal solver is implemented on distributed ML computing
platform for parallel computation of transient thermal inference
model.