Optimize Your Hybrid Multi-Cloud Deployments with NVIDIA and Capgemini Engineering


Join us for a free 1-hour session to learn how NVIDIA and Capgemini Engineering will future-proof your development and deployments in the cloud. 

From: Thursday, 21 July 2022
To: Thursday, 21 July 2022
12:00 pm - 1:00 pm Pacific Time

Developers across industries are running GPU-accelerated HPC and AI applications in the data center, on the cloud, and at the edge. However, deploying these applications on various platforms often means that the application needs to be tailored. NVIDIA’s full stack of GPUs, libraries and frameworks allows developers to build their application once and deploy it across different platforms with no code change.

A key component of this stack is the NVIDIA virtual machine image (VMI) which standardizes the development and run-time stack, enabling application deployment anywhere. In this session, you will learn:

  • What is a VMI and how the NVIDIA VMI enables seamless “lift-and-shift” across platforms
  • The difference between VMIs and containers, and how they fit in the software stack
  • How to start using the NVIDIA VMI for free today
  • How experts at Capgemini will ensure your environments are optimized for performance and flexibility 

Sign-up today to secure your spot!


Sapta Girisa, Senior Director, Capgemini Engineering

Sapta is a Sr. Director at Capgemini Engineering and leads Technical Presales and Consulting function for  Capgemini Engineering US West region. His focus is Software Product Engineering services spanning full-stack cloud-native architectures, data engineering, MLOps, and automation.  Has more than 2 decades of experience leading presales and engineering delivery across Telecommunications, Industrial IoT, and in Cloud/SaaS solutions for clients across multiple domains. Sapta holds a masters degree in Computer Science.

Chintan Patel, Sr. Manager, Product Marketing, NVIDIA

Chintan leads product marketing for NVIDIA NGC and VMI solutions. He is responsible for growing awareness and driving adoption of NVIDIA AI solutions for enterprises to take advantage of NVIDIA full stack on hybrid multi-cloud platforms. Prior to NVIDIA, he held product marketing and engineering positions at Microchip. He has an MBA from Santa Clara University and a bachelor’s degree in electrical engineering and computer science from U.C. Berkeley.

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