DI-HPC is an acceleration operator component for general algorithm modules in reinforcement learning algorithms

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

• CUDA 9.2
• PyTorch 1.5 (recommend)
• python 3.6.9
• Linux Platform

Note: We recommend that DI-HPC and DI-Engine share the same environment, and it should be fine with PyTorch from 1.3.1 to 1.8.

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-0.0.1-cp36-cp36m-linux_x86_64.whl
• di_hpc_rll-0.0.1-cp37-cp37m-linux_x86_64.whl
• di_hpc_rll-0.0.1-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