https://github.com/opendilab/di-hpc
OpenDILab RL HPC OP Lib, including CUDA and Triton kernel
https://github.com/opendilab/di-hpc
cuda hpc lstm pytorch reinforcement-learning triton
Last synced: 19 days ago
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OpenDILab RL HPC OP Lib, including CUDA and Triton kernel
- Host: GitHub
- URL: https://github.com/opendilab/di-hpc
- Owner: opendilab
- License: apache-2.0
- Created: 2021-07-05T10:15:58.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2024-07-04T08:00:02.000Z (10 months ago)
- Last Synced: 2025-04-09T21:14:45.536Z (19 days ago)
- Topics: cuda, hpc, lstm, pytorch, reinforcement-learning, triton
- Language: Python
- Homepage:
- Size: 146 KB
- Stars: 226
- Watchers: 4
- Forks: 7
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
## DI-HPC: Decision Intelligence - High Performance Computation
**DI-HPC** is an acceleration operator component for general algorithm modules in reinforcement learning algorithms, such as GAE, n-step TD and LSTM, etc. The operators support forward and backward propagation, and can be used in training, data collection, and test modules.
## Requirements
#### Setting 1
* CUDA 9.2
* PyTorch 1.5 (recommend)
* python 3.6 or python 3.7 or python3.8
* Linux Platform
#### Setting 2
* CUDA 9.0
* gcc 5.4.0
* PyTorch 1.1.0
* python 3.6 or python 3.7
* Linux Platform
*Note: We recommend that DI-HPC and DI-Engine share the same environment, and it should be fine with PyTorch from 1.1.0 to 1.10.0.*
## Quick Start
#### Install from whl
The easiest way to get DI-HPC is to use pip, and you can get `.whl` from
* [di_hpc_rll-0.0.2-cp36-cp36m-linux_x86_64.whl](http://opendilab.org/download/DI-hpc/di_hpc_rll-0.0.2-cp36-cp36m-linux_x86_64.whl)
* [di_hpc_rll-0.0.2-cp37-cp37m-linux_x86_64.whl](http://opendilab.org/download/DI-hpc/di_hpc_rll-0.0.2-cp37-cp37m-linux_x86_64.whl)
* [di_hpc_rll-0.0.2-cp38-cp38-linux_x86_64.whl](http://opendilab.org/download/DI-hpc/di_hpc_rll-0.0.2-cp38-cp38-linux_x86_64.whl)
and then call
```
$ pip install
```
#### Install from source code
Alternatively you can install latest DI-HPC from git master branch:
```
$ python3 setup.py install
```
#### Run on Linux
You will get benchmark result by following commands:
```
$ python3 tests/test_gae.py
```
## TODO
- [] Trition Kernel for Reinfocement Learning
## Feedback and Contribution
- [File an issue](https://github.com/opendilab/DI-hpc/issues/new/choose) on Github
- Discuss on DI-engine's (also for DI-hpc) [discord server](https://discord.gg/dkZS2JF56X)
- Contact our email ([email protected])
We appreciate all the feedbacks and contributions to improve DI-engine, both algorithms and system designs. And `CONTRIBUTING.md` offers some necessary information.
## License
DI-hpc released under the Apache 2.0 license.