Along with the release of the new preview of SQL Server 2017, Microsoft last week released R Server 9.1 with support for pretrained neural network models for sentiment analysis and image featurization, supports SparklyR, SparkETL, and SparkSQL, and GPU for deep neural networks.
In this update, they have made MicrosoftML algorithms portable and distributed to run on Linux, Windows, and other distributions of Hadoop — Cloudera, Hortonworks, MapR, in addition to SQL Server 2016. It comes with support for GPU-accelerated Deep Neural Networks (DNNs) with convolutions. Training a new cognitive model from scratch takes much time and effort, Microsoft is now bringing pre-trained cognitive models to R Server that accelerate time to value. These models can be re-trained and optimized for customer’s own business. R Server 9.1 now comes with high-performance operationalization which is needed by enterprises.
- Real time web services: realize 10X to 100X boost in scoring performance, scoring speeds at <10ms. Currently on Windows platform; other platforms will be supported soon.
- Role Based Access Control: enables admins to control who can publish, update, delete or consume web services
- Asynchronous batch processing: speed up the scoring performance for the web services with large input data sets and long-running jobs
- Asynchronous remote execution: run scripts in background mode on a remote server, without having to wait for the job to complete
- Dynamic scaling of operationalization grid with Azure VMs: easily spin up a set of R Server VMs in Azure, configure them as a grid for operationalization, and scale it up and down based on CPU / Memory usage