prehsept

Modeling the behaviour of primitive devices around the operating point in haskell.

Setup

Requires libtorch symlinked into the root of this repository according to extra-include-dirs and extra-lib-dirs in stack.yaml.

The setenv script can be sourced to export the correct LD_LIBRARY_PATH. Additionally it exports the DEVICE variable, supposedly enabling GPU support in Hasktorch (I'm not sure how/if it works).

$ source setenv

Usage

Build the project with stack

$ stack build

then run it

$ stack run

CLI

The executable part supports the following arguments:

Primitive Device Modeling Around the Operating Point

Usage: prehsept-exe [-k|--pdk PDK] [-d|--dev DEV] (-p|--dir DIR) [-n|--num NUM]
                    [-r|--reg REGION] [-s|--size SIZE]
  PREHSEPT

Available options:
  -k,--pdk PDK             PDK from which the data was generated
                           (default: xh035)
  -d,--dev DEV             Device Type: nmos | pmos (default: nmos)
  -p,--dir DIR             Path to lookup-table as tensor
  -n,--num NUM             Number of Epochs (default: 25)
  -r,--reg REGION          Region of Operation: 2 | 3 (default: 2)
  -e,--exp                 Experimental Mapping
  -s,--size SIZE           Batch Size (default: 5000)
  -h,--help                Show this help text

For example, to train a GPDK180 NMOS model for 100 epochs with a batch size of 32 run:

stack exec -- prehsept-exe --pdk gpdk180 --dev nmos --dir ./data/gpdk180-pmos.pt --size 32 --num 100

Notebooks

The notebooks can be viewed locally by running the jupyter server in the ./notebooks directory:

$ stack exec jupyter -- notebook

IHaskell must be installed for this to work.

License

BSD3

Thanks

Thanks to the hastorch project!