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IBM Storage and NVIDIA Deliver Reference Architectures for Accelerated and Secure ADAS/AV Development on AI Infrastructure

By VANESSA VERA NAVA posted Wed April 07, 2021 06:41 PM

  

 

IBM Storage and NVIDIA Deliver Reference Architectures for Accelerated and Secure ADAS/AV Development on AI Infrastructure

 

Developing and testing autonomous driving (AD) systems requires the analysis and storage of more data than ever before. Clients who can deliver results faster while managing rapid infrastructure growth will be the industry leaders. Without a doubt, the future of the autonomous industry is being built on AI and is heading full speed ahead. As the technology required to store data from sensors, connectivity, mapping and security rapidly expands, vehicles are becoming increasingly more data dependent. Therefore, the data platform for autonomous driving development must facilitate all operations on data—from ingestion to insight.

To deliver these operations faster, the underlying IT technology must support both new big data as well as traditional applications with security, reliability, and high performance. To handle massive, unstructured data growth, the solution must scale seamlessly while matching data value to the capabilities and costs associated with different storage tiers and types.

 

IBM Storage and NVIDIA have been working together for several years to develop reference architectures that deliver an accelerated, high-performing, scalable and secure end-to-end AI infrastructure for ADAS/AV applications. As part of next week’s NVIDIA’s GTC 2021 global event, Frank Kramer, IBM Systems Technology Architect and Thomas Schoenemeyer, Senior Solution Architect, will share how these IBM Storage and NVIDIA solutions help overcome challenges and deliver a unique value to ADAS/AV development. 

 

Register today to listen to SS33232 IBM + NVIDIA for Accelerated, High-Performing and Secure ADAS/AV Development

 

IBM Storage will also present another session at NVIDIA GTC 2021:

[SS33231] Working Together: Four Things a Data Scientist Should Demand From the Enterprise. Click to register today!

 

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