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https://github.com/cda-tum/mnt-bench

MNT Bench - An MNT tool for Benchmarking FCN circuits

https://github.com/cda-tum/mnt-bench

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 2 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: researchgate.net, springer.com, ieee.org
  • ✓
    Committers with academic emails
    1 of 2 committers (50.0%) from academic institutions
  • ✓
    Institutional organization owner
    Organization cda-tum has institutional domain (www.cda.cit.tum.de)
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (12.1%) to scientific vocabulary

Keywords

benchmarking nanocomputing physical-design

Keywords from Contributors

archival projection interactive generic sequences observability autograding hacking shellcodes modular
Last synced: 5 months ago · JSON representation

Repository

MNT Bench - An MNT tool for Benchmarking FCN circuits

Basic Info
Statistics
  • Stars: 12
  • Watchers: 2
  • Forks: 0
  • Open Issues: 0
  • Releases: 27
Topics
benchmarking nanocomputing physical-design
Created over 2 years ago · Last pushed 6 months ago
Metadata Files
Readme License

README.md

PyPI License: MIT CI Bindings codecov

MNT Bench: Layout Library for Field-coupled Nanocomputing Circuits

MNT Bench is a field-coupled nanocomputing circuit benchmark suite for multiple gate libraries and clocking schemes.

MNT Bench is part of the Munich Nanotech Toolkit (MNT) developed by the Chair for Design Automation at the Technical University of Munich and is hosted at https://www.cda.cit.tum.de/mntbench/.

This documentation explains how to use MNT Bench to filter and download benchmarks.

Benchmark Selection

So far, the functions from the following benchmark sets are implemented and provided:

  1. Trindade16
  2. Fontes18
  3. ISCAS85
  4. EPFL

Gate Libraries

So far, MNT Bench supports the following native gate-sets:

  1. ONE (for QCA) gate set: [AND, OR, NOT, BUF]
  2. Bestagon (for SiDB) gate set: [AND, NAND, OR, NOR, XOR, XNOR, NOT, BUF]

Clocking Schemes

Most of the layouts are available for any of the following clocking schemes:

| 2DDWave | ESR | | :-------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------: | | 2DDWave | ESR |

| USE | RES | | :-----------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------: | | USE | RES |

| Row | | :-----------------------------------------------------------------------------------------------------------------------: | | Row |

Repository Structure

  • src/mnt/: main source directory
  • tests: Directory for the tests for MNT Bench

Repository Usage

There are three ways how to use this benchmark suite:

  1. Via the webpage hosted at https://www.cda.cit.tum.de/mntbench/
  2. Via the pip package mnt.bench
  3. Directly via this repository

Since the first way is rather self-explanatory, the other two ways are explained in more detail in the following.

Usage via pip package

MNT Bench is available via PyPI

console (venv) $ pip install mnt.bench

Locally hosting the MNT Bench Viewer

Additionally, this python package includes the same webserver used for the hosting of the MNT Bench webpage.

After the mnt.bench Python package is installed via

console (venv) $ pip install mnt.bench

the MNT Bench Viewer can be started from the terminal via

console (venv) $ mnt.bench

This first searches for the most recent version of the benchmark files on GitHub and offers to download them. Afterwards, the webserver is started locally.

Usage directly via this repository

For that, the repository must be cloned and installed:

git clone https://github.com/cda-tum/mnt-bench.git cd mnt-bench pip install .

Afterwards, the package can be used as described above.

Owner

  • Name: Chair for Design Automation, TU Munich
  • Login: cda-tum
  • Kind: organization
  • Location: Germany

The CDA provides expertise for all main steps in the design and realization of integrated circuits, embedded systems, as well as cyber-physical systems.

GitHub Events

Total
  • Release event: 3
  • Watch event: 2
  • Delete event: 2
  • Issue comment event: 2
  • Push event: 9
  • Pull request event: 6
  • Create event: 8
Last Year
  • Release event: 3
  • Watch event: 2
  • Delete event: 2
  • Issue comment event: 2
  • Push event: 9
  • Pull request event: 6
  • Create event: 8

Committers

Last synced: 8 months ago

All Time
  • Total Commits: 89
  • Total Committers: 2
  • Avg Commits per committer: 44.5
  • Development Distribution Score (DDS): 0.09
Past Year
  • Commits: 7
  • Committers: 2
  • Avg Commits per committer: 3.5
  • Development Distribution Score (DDS): 0.143
Top Committers
Name Email Commits
Simon Hofmann s****n@t****e 81
dependabot[bot] 4****] 8
Committer Domains (Top 20 + Academic)
tum.de: 1

Issues and Pull Requests

Last synced: 8 months ago

All Time
  • Total issues: 0
  • Total pull requests: 9
  • Average time to close issues: N/A
  • Average time to close pull requests: 8 days
  • Total issue authors: 0
  • Total pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.67
  • Merged pull requests: 8
  • Bot issues: 0
  • Bot pull requests: 9
Past Year
  • Issues: 0
  • Pull requests: 2
  • Average time to close issues: N/A
  • Average time to close pull requests: 23 days
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.5
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 2
View more stats
Top Authors
Issue Authors
Pull Request Authors
  • dependabot[bot] (14)
Top Labels
Issue Labels
Pull Request Labels
dependencies (14) github_actions (13) python (1)

Dependencies

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