smartredis 0.2.0

RedisAI clients for SmartSim

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SmartRedis

SmartRedis is a collection of Redis clients that support RedisAI capabilities and include additional features for high performance computing (HPC) applications. SmartRedis provides clients in the following languages:

Language	Version/Standard
Python	3.7, 3.8, 3.9
C++	C++17
C	C99
Fortran	Fortran 2018

SmartRedis is used in the SmartSim library. SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and TensorFlow in numerical simulations at scale. SmartRedis connects these simulations to a Redis database or Redis database cluster for data storage, script execution, and model evaluation. While SmartRedis contains features for simulation workflows on supercomputers, SmartRedis is fully functional as a RedisAI client library and can be used without SmartSim in any Python, C++, C, or Fortran project.

Using SmartRedis

SmartRedis installation instructions are currently hosted as part of the SmartSim library installation instructions Additionally, detailed API documents are also available as part of the SmartSim documentation.

Dependencies

SmartRedis utilizes the following libraries.

• NumPy
• Hiredis 1.0.0
• Redis-plus-plus 1.2.3

Publications

The following are public presentations or publications using SmartRedis

• Collaboration with NCAR - CGD Seminar
• Using Machine Learning in HPC Simulations - paper (pre-print)

Cite

Please use the following citation when referencing SmartSim, SmartRedis, or any SmartSim related work.

Partee et al., “Using Machine Learning at Scale in HPC Simulations with SmartSim: An Application to Ocean Climate Modeling,” arXiv:2104.09355, Apr. 2021, [Online]. Available: http://arxiv.org/abs/2104.09355.

bibtex

```latex
@misc{partee2021using,
      title={Using Machine Learning at Scale in HPC Simulations with SmartSim: An Application to Ocean Climate Modeling},
      author={Sam Partee and Matthew Ellis and Alessandro Rigazzi and Scott Bachman and Gustavo Marques and Andrew Shao and Benjamin Robbins},
      year={2021},
      eprint={2104.09355},
      archivePrefix={arXiv},
      primaryClass={cs.CE}
}
```