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Updated 2019 02 05 (markdown)

Matthias Köfferlein 2019-02-06 01:46:36 +01:00
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2019-02-05.md

@ -207,8 +207,10 @@ Deep cont&poly ... 0.01s (sys), 1.25s (user), 1.265s (wall)
Deep cont-poly ... 0s (sys), 1.31s (user), 1.306s (wall)
```
So overall a great improvement in the hierarchical frontend layers (factor 5 to 20 in layers 1-10), a roughly factor 2 in layer 11 (metal 1) which has both hierarchical parts in the local wiring of the standard cells, but also flat parts from the power routing and pins. There is a 2-3x disadvantage of the hierarchical implementation in the flat layers (14-26) because the hierarchical analysis demands some overhead and there is no gain for the merge computation itself.
So overall a great improvement in the hierarchical frontend layers (factor 5 to 20 in layers 1-10). Still about factor 2 in layer 11 (metal 1) which has both hierarchical parts in the local wiring of the standard cells, but also flat parts from the power routing and pins. There is a 2-3x disadvantage of the hierarchical implementation in the flat layers (14-26) because the hierarchical analysis demands some overhead and there is no gain for the merge computation itself.
But the booleans pay this effort back with a 8x performance boost. That's because they are mainly frontend-driven and benefit from the hierarchical nature of the standard cells.
Total runtime of the script is in my case
* 46s (hierarchical)
* 210s (flat)