Data science professionals have been pushing the limits of IT infrastructure for decades. Dell Technologies, VMware, and NVIDIA have responded with numerous advancements in computation, data storage options, and high-speed networking to meet that challenge with fully integrated solutions. In this design guide, we show how you can manage those advances in hardware technology more efficiently, simultaneously preserving the impressive performance gains in a virtualized environment using the latest version of VMware virtualization and container software.

Nowhere have the performance advancements for data science been as rapid as the development of hardware accelerators based on the technology once used primarily for graphics processing. The Ampere GPUs from NVIDIA provide up to 20-times higher performance over the prior generation of NVIDIA GPUs. The NVIDIA A100 GPU can be partitioned up to seven GPU instances to dynamically adjust to shifting demands. With the NVIDIA AI Enterprise software suite, data scientists have the right tools and frameworks for their entire data science life cycle.

This combination of virtualized GPUs, AI enterprise software, and container orchestration in the Dell Technologies Validated Design for Virtualizing GPUs for AI with VMware and NVIDIA gives IT professionals consistent tools and processes to manage their entire data center, while allowing the data scientist to focus on data preparation and model development without worrying about the infrastructure.