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PSumSim: A Simulator for Partial-Sum Quantization in Analog Matrix-Vector Multipliers

This project includes a Python package useful for simulating partial-sum quantization in matrix-vector multipliers (MVMs) using a histogram-based data format. Written at the Institute of Microelectronics, Ulm University, Ulm, Germany by Joschua Conrad under the supervision of Prof. Maurits Ortmanns. Published at ISCAS 2025. Please acknowledge the license: {std:ref}infolicense.

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How to Cite

When using the code or concepts shown here for your own work, please cite the published paper:

bibtex @inproceedings{Conrad_PSumSim_2025, author = {Conrad, Joschua and Wilhelmstätter, Simon and Mandry, Holger and Kässer, Paul and Abdelaal, Ahmed and Asthana, Rohan and Belagiannis, Vasileios and Ortmanns, Maurits}, title = {PSumSim: A Simulator for Partial-Sum Quantization in Analog Matrix-Vector Multipliers}, booktitle = {2025 IEEE International Symposium on Circuits and Systems {(ISCAS)}}, eventtitle = {2025 IEEE International Symposium on Circuits and Systems {(ISCAS)}}, publisher = {IEEE}, location = {Londong, GB}, }

What PSumSim Can Do

• Create operands for MVM applications as numbers drawn from a random process or as histograms ({any}generateSimulationOperands)

• Implement several numeric operations on histograms

  • SQNR computation ({any}computeSqnr)
  • Quantization and clipping ({any}quantizeClipScaleValues)
  • Summation ({any}probabilisticAdder)
  • Standard-deviation computation ({any}getHistStddev)
  • Make unquantized and quantized histograms comparable ({any}equalizeQuantizedUnquantized)

• Simulate full MVM applications using stochastic processes and histograms ({any}simulateMvm). One can thereby

  • Observe full-scale values ({std:ref}maxhistvalue)
  • Observe probability for the occurence of each possible result value ({std:ref}dataformat)
  • Check a good ADC setup in terms of its full-scale ({std:ref}clipping) and bitwidth ({std:ref}quantization)
  • Check the effects of the algorithm being too large for the hardware ({std:ref}tiles)

• Explore the design-space of a MVM application regarding algorithm and hardware size and SQNR with a highly parallel simulator ({any}runAllExperiments)

• Evaluate the oprimum clipping criterion (OCC) ({any}optimumClippingCriterion)

TL;DR

Time is precious and you just want a one-liner to run in a Linux or MAC shell? Download the code, open a commandline in the directory with downloaded files and run bash python3 -m pip install --upgrade pip && \ python3 -m pip install --upgrade setuptools virtualenv wheel && \ python3 -m virtualenv venv && \ . venv/bin/activate && \ python3 -m pip install --editable ".[docs,test]" && \ sphinx-build -b html -E doc/source doc/build && \ psumsim_test && \ deactivate

This installs everything, runs tests and builds the documentation website in docs/build. You need Python3 to be installed already. Packages virtualenv, pip, setuptools and wheel are installed or upgraded system- or user-wide. But PSumSim and its dependencies are installed isolated into a folder venv.

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How to Install

This provides a python package. Downloading all files and using bash python3 -m pip install --editable . in the same directory where this README is found installs the package and allows all changes in source-files to reflect immediately. Remove the --editable switch to install the package like any other Python package, but you cannot change the provided .py files.

Also consider using a virtual environment to install packages into. This prevents any possible package-version clashes with things you already have installed.

Also consider running bash python3 -m pip install --upgrade pip setuptools wheel to upgrade the Python package-managing before installing PSumSim.

How to Use

After installing, there are several things provided by PSumSim.

Docs

To build the documentation website, first install dependencies using bash python3 -m pip install --editable ".[docs]" and again possibly ommit --editable just like in Installation Guidelines. Then, run bash sphinx-build -b html -E doc/source doc/build in the main directory. After the command completes, you'll find the documentation as a website docs/build/index.html. Add -W to fail on warnings. This README is also found there with all hyperlinks working.

Start Reading

Checkout {std:ref}concepts, which summarizes some concepts and terms used throughout the entire documentation.

Commandline

Use bash psumsim --help to get an overview over the commandline interface. This is made for running the same experiments as for the paper to get the scatter-plot data. E.g. use bash psumsim -j 4 -b 0.1 -e 0.2 to run 10% of all experiments with 4 CPU jobs. Several of these calls can be used to keep the simulation machine busy.

See {std:ref}commandlineinterface for full documentation or simply call psumsim --help. To run your own design-space exploration, check and modify {any}experiments.

As a Package

Check {any}simulateMvm, which basically is what is called for each simulated experiment. Use this in your own Python script to get histograms reflecting your own MVM application.

Tests

To simply check that the installation worked, first install test dependencies by running bash python3 -m pip install --editable ".[test]" and again possibly ommit --editable just like in Installation Guidelines. Then, run psumsim_test. Under the hood, pytest is used. Possible commandline arguments are descibed here. Common usage is to run a specific test case and exit immediately if that one fails, as run e.g. by psumsim_test -x -k "test_optimumClippingCriterion" for the test {any}test_optimumClippingCriterion.

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Acknowledgment

This work was funded by the German National Science Foundation (DFG) under grant number BE 7212/7-1 | OR 245/19-1. Furthermore, the authors acknowledge support by the state of Baden-Württemberg through bwHPC.

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