DEF parser and clustering

Usage:
    def_parser.py   [--design=DESIGN] [--clust-meth=METHOD] [--seed=<seed>] [CLUSTER_AMOUNT ...]
                    [--manhattanwl] [--mmstwl] [--cnwl] [--bb=<method>]
                    [--deffile=DEF] [--udm=VALUE] [--leftech=TECH] [--segments]
                    [--bold]
    def_parser.py (--help|-h)
    def_parser.py   [--design=DESIGN] (--digest) [--manhattanwl] [--mmstwl] [--cnwl] [--bb=<method>]
                    [--deffile=DEF] [--udm=VALUE] [--leftech=TECH] [--segments]

Options:
    --design=DESIGN         Design to cluster. One amongst ldpc, ldpc-2020, flipr, boomcore, boomcore-2020, spc,
                            spc-2020, spc-bufferless-2020, ccx, ccx-in3, ccx-in3-du10, ccx-in3-du85,
                            ldpc-4x4-serial, ldpc-4x4, 
                            ldpc-4x4-serial-2022, ldpc-4x4-serial-delBuffPy-2022, ldpc-4x4-serial-delBuff-2022, ldpc-4x4-serial-pre-CTS-2022,
                            ldpc-4x4-full-2022, ldpc-4x4-full-noFE-2022, ldpc-4x4-full-delBUFF-2022, 
                            ldpc-4x4-full-preCTS-2022, ldpc-4x4-full-delBuffPy-2022,
                            smallboom, armm0,msp430, megaboom-pp-bl, megaboom-pp-bt, 
                            mempool-tile-bl, mempool-tile-bt, mempool-group-bl, mempool-group-FP-noFE,
                            mempool-tile-post-FP, mempool-tile-post-FP-noFE, 
                            mempool-tile-pp, mempool-tile-pp-noFE.
    --clust-meth=METHOD     Clustering method to use. One amongst progressive-wl, random,
                            Naive_Geometric, hierarchical-geometric, kmeans-geometric, kmeans-random, onetoone.
                            or metal. [default: random]
    --seed=<seed>           RNG seed
    CLUSTER_AMOUNT ...      Number of clusters to build. Multiple arguments allowed.
    --manhattanwl           Compute nets wirelength as Manhattan distance.
    --mmstwl                Compute nets wirelength as MMST (Mixed Minimal Steiner Tree).
    --cnwl                  Compute nets wirelength as Closest Neighbourg (slower, but more accurate).
    --bb=<method>           Bounding box computation method: cell or pin.
    --digest                Print design's info and exit.
    --deffile=DEF           Path to DEF file, superseded by --design.
    --udm=VALUE             UNITS DISTANCE MICRONS, e.g. 10000, superseded by --design
    --leftech=TECH          LEF tech used, e.g. 7nm, superseded by --design
    --segments              Compute the Manhattan segment length of each net into WLnets_wegments.out
    --bold                  Suppress the clustering sanity checks
    -h --help               Print this help

Input files

DEF

This script needs a fully placed and routed design as a DEF file.

LEF

Technology file, needed for the geometry and names of the standard cells.

Output files

CellCoord.out

Each line is <net name>, <instance name>, <x coordinate [float]>, <y coordinate [float]>.

InstancesPerNet.out

Each line is <net name> <instance name 1> <...> <instance name n>.

Nets.out

Each line is <net name>.

WLnets.out

Header: NET NUM_PINS LENGTH

Then each line is <net name> <number of pins [integer]> <length in µm [float]>.

Design_net_wl.csv

The nets are first sorted based on their length.

Header: Net_name net_wire_length cumulated_wire_length %_of_nets.

• Column 1: name of the net
• Column 2: length of the net in µm [float]
• Column 3: Cumulated total wire length in µm of the nets so far. This should be equal to the design total wire length for the last line.
• Column 4: Percentage of the total amount of nets so far. This should be equal to 100% for the last line.

Clusters.out

Each line: <cluster name>

In all the custom clustering methods, the cluster name is its ID, starting at 0 then incrementing by 1.

ClustersArea.out

Header: Name Type InstCount Boundary Area

• Column 1: <cluster name>, same as in Clusters.out
• Column 2: Type of cluster, exclusive by default.
• Column 3: Amount of instances in the cluster [integer]
• Column 4: Coordinates of the cluster's bottom left corner, (<x coordinate [float]>,<y coordinate [float]>)
• Column 5: Coordinates of the cluster's top right corner, (<x coordinate [float]>,<y coordinate [float]>) Columns 4 and 5 only make sense if the cluster is rectangular shaped.
• Column 6: area of the cluster in µm2 [float]

ClustersInstances.out

Each line: <cluster name> <instance name 1> <...> <instance name n>.