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Signed-off-by: Csaba Kiraly <csaba.kiraly@gmail.com> |
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DAS | ||
doc | ||
.gitignore | ||
LICENSE-APACHEv2 | ||
LICENSE-MIT | ||
README.md | ||
smallConf.py | ||
study.py |
README.md
DAS Research
This repository hosts research on DAS for the collaboration between Codex and the EF.
The goal of the DAS Simulator is to study the problem of Data Availability Sampling, both as it is currently proposed and with possible modifications, from the networking perspective. The simulator is written in Python3 for accessibility, but we can imagine rewriting it at one point for scalability and efficiency.
Currently we simulate the first part of the process which is to get segments of the 2D Reed Solomon erasure coded block from the block builder to validators. The simulator tracks diffusion in the network and validation progress. It is highly configurable, and it allows to explore the parameter space in one run, generating also summary figures.
Talks
Results from the simulator were featured in the following talks:
- EthereumZuri.ch 2023 - Csaba Kiraly - Data Availability Sampling from the Networking Perspective, see on YouTube
- EDCON 2023 - Leonardo Bautista-Gomez - Understanding Design Choices in Data Availability Sampling see on YouTube
- EthPrague 2023 - Leonardo Bautista-Gomez - Understanding Design Choices in Data Availability Sampling see on YouTube
- EthCC 2023 - Csaba Kiraly - Understanding Design Choices in Data Availability Sampling see on YouTube
Versions
For recent improvements, see the develop branch
Usage
Prepare the environment
- Clone the DAS repository (if not done yet) and go into the das-research directory
git clone https://github.com/status-im/das-research.git
cd das-research
- Create a virtual environment and install the requirements
python3 -m venv myenv
source myenv/bin/activate
pip3 install -r DAS/requirements.txt
Run the simulator
The simulation requires a configuration written in Python. To run a small example, use the smallConf.py
configuration file:
python3 study.py smallConf.py
Results with plots will be saved in the results
folder.
See the same example smallConf.py
file for the description of configuration options. To derive your own simulations, copy the file, customize, and run.
License
Licensed and distributed under either of
- MIT license: LICENSE-MIT or https://opensource.org/licenses/MIT
or
- Apache License, Version 2.0: LICENSE-APACHEv2 or https://www.apache.org/licenses/LICENSE-2.0
at your option. Files in this repository may not be copied, modified, or distributed except according to those terms.