This commit is contained in:
yueguoguo 2017-08-18 18:38:23 +08:00
Родитель 4dc8a26f71 a4d5e84be9
Коммит 7d6c858ba8
1 изменённых файлов: 4 добавлений и 2 удалений

Просмотреть файл

@ -25,14 +25,16 @@ Microsoft R extensions.
* Elasiticity
* Deployment of a DSVM with customized information such as machine name, machine size, operating system, authentication method, etc.
* Deployment of a DSVM with customized information such as machine name, machine size (with compute/memory optimized general-purpose CPU, Nvidia K80/M60 GPU, etc.), operating system (Windows Server 2016, Ubunbut 16.04, and CentOS), authentication method (public key based or password based), etc.
* Enjoy all benefits of a Windows/Linux DSVM. E.g., all tools for data science work such as R/Python/Julia programming languages, SQL Server, Visual Studio with RTVS, etc., remote working environment via RStudio Server or Jupyter Notebook interface, and machine learning & artificial intelligence packages such as Microsoft CNTK, MXNet, and XGBoost.
* Execution of R analytics on DSVM(s) with various Microsoft R Server computing contexts such as "local parallel" and "cluster parallel".
* Seamless interaction with remote R Server session with `mrsdeploy` functions.
* Post-deployment installation of extension for customizing system environment, reinstalling/uninstalling software, etc.
* Scalability
* Deployment of a collection of heterogeneous DSVMs for a group of data scientists.
* Scale up DSVM and form them into a cluster for parallel computation with Microsoft R Server backend.
* Scale up DSVM and form them into a cluster for parallel/distributed computation with Microsoft R Server backend.
* Usability