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Domino Data Lab Unveils NVIDIA-Powered Data Science MLOps Tools

Domino Data Lab Unveils NVIDIA-Powered Data Science MLOps Tools

Source: Domino Data Lab

Domino Data Lab recently announced a series of new integrated solutions and product enhancements with NVIDIA, according to a press release. The technologies were unveiled at the NVIDIA GTC Conference. Domino’s latest is highlighted by Domino’s availability for the NetApp ONTAP AI Integrated Solution, which upgrades data science productivity with software that streamlines the workflow while maximizing infrastructure utilization. As such, Domino has been tested and validated to run on the packaged offering and is available via the NVIDIA Partner network.

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Domino Data Lab is an enterprise data science platform that allows data scientists to build and run predictive models. The product helps organizations with the development and delivery of these models via infrastructure automation and collaboration. Domino provides users access to a Data Science Workbench that provides open source and commercial tools for batch experiments, as well as Model Delivery so they can publish APIs and web apps or schedule reports.

The new platform automatically creates and manages multi-node clusters and releases them when training is done. Domino currently supports ephemeral clusters using Apache Spark and Ray, and will be adding support for Dask in a product release later in the year. Administrators can also divide a single NVIDIA DGX A100 GPU into multiple instances or partitions to support a variety of users with Domino’s support. According to the announcement, this allows “7x the number of data scientists to run a Jupyter notebook attached to a single GPU versus without MIG.”

Domino also enables customers to create framework-specific custom work environments based on NGC containers, which include RAPIDS, TensorFlow, PyTorch, CUDA, and more.

NVIDIA GTC runs through Friday April 16, check out the keynote.

The post Domino Data Lab Unveils NVIDIA-Powered Data Science MLOps Tools appeared first on Best Business Intelligence and Data Analytics Tools, Software, Solutions & Vendors .

Auteur d'origine: Timothy King
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