Fibertree/Timeloop/Accelergy Tutorial Exercises

This repository contains a set of exercises and baseline designs to explore Fibertrees, Timeloop, and Accelergy. Please find the respective directories and more detailed descriptions under workspace folder.

Using Docker

We provide a docker with built-in tools for you to get started

• Make a copy of the provided template docker compose file: cp docker-compose.yaml.template docker-compose.yaml
• Examine the instructions in docker-compose.yaml to setup the docker correctly, e.g., setup the correct UID and GID.
• Pull the newest docker image: docker-compose pull
• Run docker: docker-compose up. You should see the docker being setup.
• This docker uses Jupyter notebooks, and you will see an URL once the docker is up. Please copy and paste the URL to a web browser of your choice to access the workspace.

Notes (if notebook URL does not work)

• Option1: in your docker-compose.yaml file, uncomment the last line under environment to disable token and try again
• Option2: try the 192.168.X.X host with the same token as shown in the output (X.X can be obtained by hostname -I)
• Option3: if you have access to docker GUI app (e.g., Kitematic for docker temrinal), try open the web page there with the token

Native Installation

Please find the instructions for native installations of the tools needed here

Related reading

• Timeloop/Accelergy documentation
• Timeloop/Accelergy tutorial
• SparseLoop tutorial
• eyeriss-like design
• simba-like architecture

Citation

Please cite the following:

• A. Parashar, P. Raina, Y. S. Shao, Y.-H. Chen, V. A. Ying, A. Mukkara, R. Venkatesan, B. Khailany, S. W. Keckler, and J. Emer, “Timeloop: A systematic approach to DNN accelerator evaluation,” in 2019 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), 2019, pp. 304–315.
• M. Horeni, P. Taheri, P. Tsai, A. Parashar, J. Emer, and S. Joshi, “Ruby: Improving hardware efficiency for tensor algebra accelerators through imperfect factorization,” in 2022 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), 2022, pp. 254–266.
• Y. N. Wu, P.-A. Tsai, A. Parashar, V. Sze, and J. S. Emer, “Sparseloop: An analytical, energy-focused design space exploration methodology for sparse tensor accelerators,” in 2021 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), 2021, pp. 232–234.
• Y. N. Wu, J. S. Emer, and V. Sze, “Accelergy: An architecture-level energy estimation methodology for accelerator designs,” in 2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2019, pp. 1–8.
• T. Andrulis, J. S. Emer and V. Sze, "CiMLoop: A Flexible, Accurate, and Fast Compute-In-Memory Modeling Tool," in 2024 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), 2024, pp. 10-23.

Or use the following BibTeX:

@inproceedings{timeloop,
  author      = {Parashar, Angshuman and Raina, Priyanka and Shao, Yakun Sophia and  Chen, Yu-Hsin and Ying, Victor A and Mukkara, Anurag and Venkatesan, Rangharajan and Khailany, Brucek and Keckler, Stephen W and Emer, Joel},
  booktitle   = {2019 IEEE international symposium on performance analysis of systems and software (ISPASS)}, pages={304--315}, year={2019},
  title       = {Timeloop: A systematic approach to dnn accelerator evaluation},
  year        = {2019},
}
@inproceedings{ruby,
  author      = {M. Horeni and P. Taheri and P. Tsai and A. Parashar and J. Emer and S. Joshi},
  booktitle   = {2022 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)},
  title       = {Ruby: Improving Hardware Efficiency for Tensor Algebra Accelerators Through Imperfect Factorization},
  year        = {2022},
}
@inproceedings{sparseloop,
  author      = {Wu, Yannan N. and Tsai, Po-An, and Parashar, Angshuman and Sze, Vivienne and Emer, Joel S.},
  booktitle   = {{ ACM/IEEE International Symposium on Microarchitecture (MICRO)}},
  title       = {{Sparseloop: An Analytical Approach To Sparse Tensor Accelerator Modeling }},
  year        = {{2022}}
}
@inproceedings{accelergy,
  author      = {Wu, Yannan Nellie and Emer, Joel S and Sze, Vivienne},
  booktitle   = {2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)},
  title       = {Accelergy: An architecture-level energy estimation methodology for accelerator designs},
  year        = {2019},
}
@inproceedings{cimloop,
  author      = {Andrulis, Tanner and Emer, Joel S. and Sze, Vivienne},
  booktitle   = {2024 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)}, 
  title       = {{CiMLoop}: A Flexible, Accurate, and Fast Compute-In-Memory Modeling Tool}, 
  year        = {2024},
}