Probabilistic Computing Project

This repository contains implementations and tools for probabilistic computing using p-bits. The setup instructions below will guide you through cloning the repository, setting up a virtual environment, and ensuring proper configuration for running the project.

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1. Clone the Repository

First, clone the repository to your local machine:

git clone https://github.com/YOUR_GITHUB_USERNAME/YOUR_REPO_NAME.git
cd YOUR_REPO_NAME

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2. Create and Activate the Virtual Environment

Ensure you have Python 3.8+ installed, then create a virtual environment:

python -m venv .venv

Windows

.venv\Scripts\activate

✅ If you see .venv in your terminal prompt, your environment is activated!

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3. Run Setup Script for PYTHONPATH

This script ensures your project directory is included in PYTHONPATH automatically. Append the working directory to the venv activate.bat and Activate.ps1 files.

Windows

post-venv-setup.bat

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4. Install Dependencies

Run the following command to install all required Python packages:

pip install -r requirements.txt

If using Poetry, install dependencies with:

poetry install

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5. Verify Setup

Run these tests to confirm everything is working:

Check Python Path

python -c "import sys; print(sys.path)"

You should see a path similar to:

'C:\repositories\ProbabilisticComputing'

Check if Dependencies are Installed

python -c "import numpy; import pandas; import matplotlib; print('All packages installed!')"

If everything is correct, you’ll see:

All packages installed!

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6. Running the Project

To run your scripts or Jupyter Notebooks, first activate the virtual environment:

.venv\Scripts\activate  # Windows
source .venv/bin/activate  # macOS/Linux

Then execute:

python your_script.py

or open Jupyter Notebook:

jupyter notebook

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7. Deactivating the Virtual Environment

When you're done, deactivate the virtual environment:

deactivate

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Troubleshooting

PYTHONPATH Not Set?

If PYTHONPATH is not set, manually run:

echo $PYTHONPATH  # macOS/Linux
echo %PYTHONPATH%  # Windows

If empty, re-run:

bash post-venv-setup.sh  # macOS/Linux
post-venv-setup.bat  # Windows

Issues with Dependencies?

Ensure all dependencies are installed:

pip install -r requirements.txt

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Using the scripts

Python scripts placed under the Scripts folder are used to generate parameters, simulate the probabilistic circuit, and plotting the output.

Overview

• comparison.py
  Loads CSV data from FPGA and Python Boltzmann simulations, merges them based on common labels, and generates plots comparing normalized probability distributions. It supports saving the plots automatically.

• CustomScripts.py
  Contains utility functions for:

  • Converting between bipolar and binary representations.
  • Calculating fixed-point ranges.
  • Generating SystemVerilog initialization code (e.g., seed generation, parameter formatting).

• generate_bar_plots.py
  Reads simulation output CSV files, processes the data according to a provided label mapping, and generates bar plots showing the probability distribution of output cases. It can also export the computed counts to CSV.

• generate_weight_from_logic.py
  Scans a designated Circuit_Library folder for NPZ files containing circuit weight data, extracts bias vectors (h) and weight matrices (J), and constructs a weight library. It also includes a function to compute overall circuit weights from a logic circuit description.

• simulate_p_circuit.py
  Implements functions to:

  • Compute binary energy for given states.
  • Generate Boltzmann distributions based on Ising-like energy models.
  • Simulate p-bit dynamics using both iterative updates and direct Boltzmann sampling.
  • Plot the resulting probability distributions from simulations.