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https://github.com/maestro-project/maestro
An analytical cost model evaluating DNN mappings (dataflows and tiling).
https://github.com/maestro-project/maestro
dataflow deep-learning deep-neural-networks
Last synced: about 2 months ago
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An analytical cost model evaluating DNN mappings (dataflows and tiling).
- Host: GitHub
- URL: https://github.com/maestro-project/maestro
- Owner: maestro-project
- License: mit
- Created: 2019-06-01T21:23:04.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2024-04-15T11:49:39.000Z (8 months ago)
- Last Synced: 2024-08-01T16:48:59.235Z (5 months ago)
- Topics: dataflow, deep-learning, deep-neural-networks
- Language: MATLAB
- Homepage: http://maestro.ece.gatech.edu
- Size: 743 KB
- Stars: 173
- Watchers: 7
- Forks: 55
- Open Issues: 18
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-approximate-dnn - Maestro - open-source tool for modeling and evaluating the performance and energy-efficiency of different dataflows for DNNs (Tools / FPGA based accelerator / HLS for CNNs)
- awesome-opensource-hardware - maestro
README
# MAESTRO: An Open-source Infrastructure for Modeling Dataflows within Deep Learning Accelerators
[](./LICENSE)
# What is MAESTRO?
MAESTRO is an open-source tool for modeling and evaluating the performance and energy-efficiency of different dataflows. MAESTRO is actively developed by the [Synergy Lab](https://synergy.ece.gatech.edu/) at [Georgia Institute of Technology](https://www.gatech.edu/). For more details about MAESTRO, please visit the following links.
- [MAESTRO Website](http://maestro.ece.gatech.edu/)
- [MAESTRO Docs](http://maestro.ece.gatech.edu/docs/build/html/index.html)
# Codebase
## Updates
### May 26th, 2021
We updated the hardware description file, added off-chip bandwidth added as constraint.
We added a validation folder with data for Eyeriss and MAERI from MICRO 2019 paper.
### Oct 13th, 2020
We added a direct support for GEMM layers. For more information, please take a look at [here](http://maestro.ece.gatech.edu/docs/build/html/layer_supported.html).
### May 13th, 2020
We updated the naming convention of mappings and the directory structure of data folder.
### Oct 14th, 2019
Latest codebase released along with MAESTRO MICRO 2019 paper.
## Maintainers
- Felix (Sheng-Chun) Kao ([email protected])
- Geonhwa Jeong ([email protected])
- Tushar Krishna ([email protected])
## Technical Contributors
- Hyoukjun Kwon (Georgia Tech, now at Facebook Reality Labs): Main developer (core framework and functionalities)
- Prasanth Chatarasi (Georgia Tech, now at IBM Research): APIs + interface to mapping optimizers.
- Felix (Sheng-Chun) Kao (Georgia Tech): Pytorch frontend + updates to cost-model/interface + GAMMA mapper
- Geonhwa Jeong (Georgia Tech): Keras frontend + debugging + website maintainer.
- Saurabh Malik (Georgia Tech, now at Microsoft): Jupyter Notebooks demo + website.
# Citations ###
```
@inproceedings{maestro_micro2019,
author = {Hyoukjun Kwon and
Prasanth Chatarasi and
Michael Pellauer and
Angshuman Parashar and
Vivek Sarkar and
Tushar Krishna},
title = {Understanding Reuse, Performance, and Hardware Cost of {DNN} Dataflow:
{A} Data-Centric Approach},
booktitle = {Proceedings of the 52nd Annual {IEEE/ACM} International Symposium
on Microarchitecture, {MICRO}},
pages = {754--768},
publisher = {{ACM}},
year = {2019},
}
```
```
@article{maestro_toppicks2020,
author = {Hyoukjun Kwon and
Prasanth Chatarasi and
Vivek Sarkar and
Tushar Krishna and
Michael Pellauer and
Angshuman Parashar},
title = {{MAESTRO:} {A} Data-Centric Approach to Understand Reuse, Performance,
and Hardware Cost of {DNN} Mappings},
journal = {{IEEE} Micro},
volume = {40},
number = {3},
pages = {20--29},
year = {2020},
}
```