Nvidia to Launch Enterprise AI Data Platform Ontap AI

The basis of the platform is the supercomputers DGX-1 and cloud flash storages AFF A800
03 August 2018   252

NVIDIA and NetApp launched the corporate platform Ontap AI to store models of artificial intelligence. Unlike cloud services, it is equipped with tools for accelerated collection, processing and transmission of data. This is reported by Venture App.

The basis of the platform is the supercomputers DGX-1 and cloud flash storages AFF A800. To distribute data over the clouds and provide quick access, regardless of format and location, the Data Fabric architecture is used.

The NVIDIA DGX-1 computers support second-generation in-depth training and are equipped with Tesla V100 graphics cards. One DGX-1 rack provides 1 Pflops of power and is able to train the FairSeq Neural Network presented in May 2017 for one and a half days. The AFF A800 drives in a cluster with 24 nodes read data at 300 GB / s and have a delay of 200 μs.

The Ontap AI platform was already used in the consulting firm Cambridge Consultants. It was involved in the development of systems for studying the effects of drugs on patients. Also Ontap AI was used to create Vincent - a painting training program at the level of human capabilities.

In April 2018, NVIDIA CEO Jensen Huang announced that their video cards no longer comply with Moore's law. With the help of the DGX-2 supercomputer, the company managed to train the AlexNet neural network to store 15 million images in 18 minutes.

Oracle to Open GraphPipe Source Code

GraphPipe is a tool that simplifies the maintenance of machine learning models
17 August 2018   136

Oracle has opened the source code of the GraphPipe tool to simplify the maintenance of machine learning models. It supports projects based on the TensorFlow, MXNet, Caffe2 and PyTorch libraries. They are intended for use in IoT-devices, custom web-services and corporate AI-platforms.

The tool eliminates the need for developers to create custom APIs. Also, it eliminates confusion when using multiple frameworks and prevents memory copying during deserialization. The developers hope that GraphPipe will become a standard tool for deploying models.

GraphPipe is free and available on GitHub. It consists of open source tools designed to work with artificial intelligence. For example, the TensorFlow framework and the Open Neural Network Exchange (ONNX) project for creating portable neural networks are among them.

In September 2017, Microsoft introduced own tools for operating with machine learning. At the same time, the company released utilities for using Visual Studio Code when creating models based on the CNTK and Keras frameworks.