RD-Gen

    

About

RD-Gen (random DAG generator considering multi-rate applications for reproducible scheduling evaluation) is a tool for researchers targeting DAGs. RD-Gen makes the following contributions:

• RD-Gen extends existing random DAG construction methods, Fan-in/Fan-out [1] and G(n, p) [2] methods, to meet researchers’ requirements.
• RD-Gen proposes a new Chain-based method to flexibly construct state-of-the-art chain-based multi-rate DAGs.
• RD-Gen reduces implementation effort through the automatic setting of complex parameters and batch generation of random DAG sets.

Setup flow

$ git clone https://github.com/azu-lab/RD-Gen.git
$ cd RD-Gen
$ ./setup.bash

Quick start

Sample config files can be used without modification.

Chain-based method

$ python3 run_generator.py -c ./sample_config/chain_based/sample_chain_based.yaml

Fan-in/Fan-out method

$ python3 run_generator.py -c ./sample_config/fan_in_fan_out/sample_fan_in_fan_out.yaml

G(n, p) method

$ python3 run_generator.py -c ./sample_config/g_n_p/sample_g_n_p.yaml

Documents

• wiki
• API list (for developer)
• RD-Gen is presented in the following paper:

  • A. Yano and T. Azumi, "RD-Gen: Random DAG Generator Considering Multi-rate Applications for Reproducible Scheduling Evaluation", the 26th IEEE International Symposium on Real-Time Distributed Computing (ISORC), 2023

    BibTeX

    @inproceedings{RD-Gen,
      title={{RD-Gen}: Random {DAG} Generator Considering Multi-rate Applications for Reproducible Scheduling Evaluation},
      author={Atsushi, Yano and Takuya, Azumi},
      booktitle={Proceedings of the 26th IEEE International Symposium on Real-Time Distributed Computing (ISORC)},
      year={2023},
      organization={IEEE}
    }

References

• [1] R. P. Dick, D. L. Rhodes, and W. Wolf. TGFF: task graphs for free. In Proc. of Workshop on CODES/CASHE, 1998.
• [2] Daniel Cordeiro, Gregory Mounie, Swann Perarnau, Denis Trystram, Jean-Marc Vincent, and Frederic Wagner. Random graph generation for scheduling simulations. In Proc. of SIMUTools, 2010.