Menu

M2M FEATURE NEWS

MapR Announces Complementary Data Management and Logistics for NVIDIA Software

By Ken Briodagh October 15, 2018

According to a recent announcement, MapR Technologies, provider of a data platform for Artificial Intelligence (AI) and Analytics, will now support data access and production deployments for data science through the NVIDIA RAPIDS open-source software.

MapR helps data scientists accelerate the access of required training data by focusing on easing the issues of on-boarding, cleansing, cataloging, and feeding data at high performance to GPUs and NVIDIA DGX systems. The MapR solution also manages the deployment and management of multiple models into production to speed business impact.

“The challenge for most data scientists is the data logistics to locate, prep and access the right data for training. In many cases, 90 percent of the time is spent data wrangling,” said Anil Gadre, EVP and chief product officer, MapR Technologies. “MapR complements RAPIDS with a data management and logistics fabric to accelerate the high-scale processing and access of disparate data across geographies. The same fabric also speeds the deployment of models into production and coordinates the continuous deployment and updating of multiple models to impact business in real-time at scale.”

Central to the solution is the ability to coordinate data flows from across the enterprise and, through a pre-built MapR container for GPUs, make it easy to integrate into NVIDIA’s complete end-to-end data science training pipelines. The MapR Data Platform for RAPIDS is designed to enable data scientists to:

  • Collect data at scale from a variety of sources and preserve raw data so that potentially valuable features are not lost
  • Make input and output data available to many independent applications even across geographically distant locations, on premises, in the cloud or at the edge
  • Manage multiple models during development and easily roll into production
  • Improve evaluation methods for comparing models during development and production, including use of a reference model for baseline successful performance
  • Support rapid stream-based delivery of standard files including Parquet, ORC, JSON, AVRO, and CSV file formats directly into RAPIDS

“MapR’s work with NVIDIA in the RAPIDS ecosystem is helping make broad adoption in the enterprise easy for the largest breadth of workloads,” said Clément Farabet, VP, AI infrastructure, NVIDIA. “MapR’s ability to span on-prem and cloud, from IoT edge to core with a scalable, high-performance common platform means that more data can be fed to GPUs and more innovative applications can be created by data scientists faster.”


Ken Briodagh is a writer and editor with more than a decade of experience under his belt. He is in love with technology and if he had his druthers would beta test everything from shoe phones to flying cars.

Editorial Director

SHARE THIS ARTICLE
Related Articles

The Internet of Things and the Cloud

By: Special Guest    4/17/2019

The cloud is a huge, interconnected network of powerful servers that performs services for businesses and for people.

Read More

Wireless Broadband Alliance and Mettis Aerospace Announce Wi-Fi 6 IoT Trial

By: Ken Briodagh    4/17/2019

The Wireless Broadband Alliance recently announced its first Wi-Fi 6 Industrial Enterprise and IoT trial, as part of its ongoing Wi-Fi 6 program.

Read More

Digi International Brings CAT11 to Enterprise Cellular Extenders with Digi EX15

By: Ken Briodagh    4/16/2019

CAT11-capable Cellular Extender Provides LTE Connectivity for Business Continuity in the Storefront, Branch Office and Beyond

Read More

The Future is Hyper-Connected

By: Special Guest    4/15/2019

Companies have new opportunities to reach existing customers and build revenue streams in new markets thanks to interfaces ranging across NB-IOT, 4G, …

Read More

ON Semiconductor Advances Battery-Less IoT with Bluetooth Low Energy Multi-Sensor Platform

By: Ken Briodagh    4/11/2019

ON Semiconductor recently released its new RSL10 Multi-Sensor Platform powered with a solar cell, designed to support the development of IoT sensors u…

Read More