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Things to Know When Assessing, Piloting, and Deploying GPUs

Scaling your GPU deployments

Traditionally, graphical processing units, or GPUs, were used in processing 3D content/data in gaming. Today, GPUs have become a key technology for applications in manufacturing, life sciences, and financial modeling. GPUs speed up simulations due to their fast parallel processing capabilities and are now being used extensively in Artificial Intelligence (AI) and Machine Learning (ML) applications. Creating a large-scale environment that utilizes GPUs takes planning, piloting, implementing at scale, and, finally, evaluation. 

For an effective production environment using GPUs, organizations need a defined process that contains the Assessment, the pilot program and scaling implementation for anticipated workloads.

This paper will help you plan the process and make sure your deployment is successful.

Things to Know When Assessing, Piloting, and Deploying GPUs
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Scaling your GPU deployments

Traditionally, graphical processing units, or GPUs, were used in processing 3D content/data in gaming. Today, GPUs have become a key technology for applications in manufacturing, life sciences, and financial modeling. GPUs speed up simulations due to their fast parallel processing capabilities and are now being used extensively in Artificial Intelligence (AI) and Machine Learning (ML) applications. Creating a large-scale environment that utilizes GPUs takes planning, piloting, implementing at scale, and, finally, evaluation. 

For an effective production environment using GPUs, organizations need a defined process that contains the Assessment, the pilot program and scaling implementation for anticipated workloads.

This paper will help you plan the process and make sure your deployment is successful.