Unverified Commit 3cbb044f by ZhiangWang033 Committed by GitHub

Update README.md

parent a70f3fa2
......@@ -5,11 +5,23 @@ runtimes. Gridding enables hard macros to find locations consistent with high so
Gridding determines a dissection of the layout canvas into some number of rows (**n_rows**) and some number of columns (**n_cols**) of _gridcells_.
The choice of **n_rows** and **n_cols** is made **once** for each design. Once the dimensions **(n_rows, n_cols)** have been chosen, their values define a gridded canvas, or _grid_, and remain fixed throughout Circuit Training for the given design.
The choice of **n_rows** and **n_cols** is made **once** for each design. Once the dimensions **(n_rows, n_cols)** have been chosen, their values define a gridded canvas, or _grid_, and remain fixed throughout Circuit Training for the given design.
The detailed algorithm is shown as following.
<img src="./Gridding Algorithm.png" width= "1600"/>
The gridding algorithm starts with the dimensions **canvas_width** and **canvas_height** of the layout canvas, as well as a list of **macros**, where each macro has a width and a height.
Macros are not rotatable. The area of a macro is the product of its width and height.
Then, the gridding searches over combinations (**n_rows**, **n_cols**), with constraints
- **min_n_rows** <= **n_rows** < **max_n_rows**
- **min_n_cols** <= **n_cols** < **max_n_cols**
- **min_num_gridcells** <= **n_rows** * **n_cols** <= **max_num_grid_cells**
- **grid_w** / **grid_h** <= **max_aspect_ratio**
- **grid_h** / **grid_w** <= **max_aspect_ratio**
- The macros can be packed sequentially on the gridcells. There are **n_rows** * **n_cols** gridcells in the canvas. \[Algorithm 1 Lines 11-22\]
where each gridcell has width of **grid_w** = **canvas_width** / **n_cols**
and height of **grid_h** = **canvas_height** / **n_row**.
The main idea is to search for a particular (**n_rows**, **n_cols**) combination
that maximize the metric related to wasted space.
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