Metadata-Version: 2.1
Name: smartredis
Version: 0.4.2
Summary: RedisAI clients for SmartSim
Home-page: https://github.com/CrayLabs/SmartRedis
Author: CrayLabs, a Hewlett Packard Enterprise OSS Organization
Author-email: craylabs@hpe.com
License: BSD 2-Clause License
Project-URL: Source, https://github.com/CrayLabs/SmartRedis
Project-URL: Documentation, https://www.craylabs.org
Description: 
        
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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, 3.10                          |
        | C++        |   C++17                                        |
        | C          |   C99                                          |
        | Fortran    |   Fortran 2018 (GNU/Intel), 2003 (PGI/Nvidia)  |
        
        SmartRedis is used in the [SmartSim library](https://github.com/CrayLabs/SmartSim).
        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](https://www.craylabs.org/docs/installation_instructions/basic.html#smartredis)
        Additionally, detailed [API documents](https://www.craylabs.org/docs/api/smartredis_api.html) are also available as
        part of the SmartSim documentation.
        
        ## Dependencies
        
        SmartRedis utilizes the following libraries:
        
         - [NumPy](https://github.com/numpy/numpy)
         - [Hiredis](https://github.com/redis/hiredis) 1.1.0
         - [Redis-plus-plus](https://github.com/sewenew/redis-plus-plus) 1.3.5
        
        ## Publications
        
        The following are public presentations or publications using SmartRedis
        
         - [Collaboration with NCAR - CGD Seminar](https://www.youtube.com/watch?v=2e-5j427AS0)
         - [Using Machine Learning in HPC Simulations - paper](https://www.sciencedirect.com/science/article/pii/S1877750322001065)
         - [Relexi — A scalable open source reinforcement learning framework for high-performance computing - paper](https://www.sciencedirect.com/science/article/pii/S2665963822001063)
        
        ## Cite
        
        Please use the following citation when referencing SmartSim, SmartRedis, or any SmartSim related work:
        
            Partee et al., "Using Machine Learning at scale in numerical simulations with SmartSim:
            An application to ocean climate modeling",
            Journal of Computational Science, Volume 62, 2022, 101707, ISSN 1877-7503.
            Open Access: https://doi.org/10.1016/j.jocs.2022.101707.
        
        ### bibtex
        
            @article{PARTEE2022101707,
                title = {Using Machine Learning at scale in numerical simulations with SmartSim:
                An application to ocean climate modeling},
                journal = {Journal of Computational Science},
                volume = {62},
                pages = {101707},
                year = {2022},
                issn = {1877-7503},
                doi = {https://doi.org/10.1016/j.jocs.2022.101707},
                url = {https://www.sciencedirect.com/science/article/pii/S1877750322001065},
                author = {Sam Partee and Matthew Ellis and Alessandro Rigazzi and Andrew E. Shao
                and Scott Bachman and Gustavo Marques and Benjamin Robbins},
                keywords = {Deep learning, Numerical simulation, Climate modeling, High performance computing, SmartSim},
                }
        
Keywords: redis,clients,hpc,ai,deep learning
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: BSD License
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Requires-Python: <3.11,>=3.7
Description-Content-Type: text/markdown
Provides-Extra: dev
Provides-Extra: doc
Provides-Extra: xarray
