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Running Deep Learning Workloads in the Modern AI Data Center

Enterprise and hyperscale data centers are increasingly being built around workloads using AI and deep neural networks (DNNs) with massive amounts of data. The level of computation required is significant—and would benefit greatly from the power of GPUs. Data centers that support GPU servers provide much higher efficiency and performance, use less power for advanced workloads, and require less floor space.

Learn the best practices for making a data center “GPU-ready,” with a focus on power, cooling, and architecture, including rack layout, storage, and system and network architecture. By exploring computationally intensive workloads on NVIDIA® DGX-1 and NVIDIA® Tesla® V100 GPUs, this paper will guide you through how to minimize spend and how to run today’s advanced workloads at scale.

Considerations for Scaling GPU-Ready Data Centers Technical Overview

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