Performance Intensive Computing

To compete in the marketplace, enterprises are increasingly employing performance-intensive tools and applications like machine learning, artificial intelligence, data-driven insights and automation to differentiate their products and services. In doing so, they may be unintentionally backing into performance-intensive computing because these technologies are computationally and/or data intensive.

A video discussion between Charles Liang, Supermicro CEO, and Dr. Lisa Su, AMD CEO.  

The CPU package is configurable at time of purchase with various options that you can match up to the specific characteristics of your workloads. Ask yourself the three questions the story poses.

AI architecture must scale effectively without sacrificing cost efficiency. One size does not fit all.

The modern data center must be both highly performant and energy efficient. Massive amounts of data are generated at the edge and then analyzed in the data center.

Today’s data center has numerous challenges: provisioning hardware and cloud workloads, balancing the needs of performance-intensive applications across compute, storage and network resources, and having a consistent monitoring and analytics framework to feed intelligent systems management.

Last week, Supermicro announced its new H13 A+ server solutions, featuring the latest fourth-generation AMD EPYC™ processors.

Google Cloud has been working over the past several years with AMD on developing new on-chip security protocols. More on the release of the AMD EPYC™ 9004 series processors in this part three of a four-part series..

Organizations around the world are requiring new options for their next-generation computing environments. Mid-size organizations, in particular, are facing increasing pressure to deliver cost-effective, high-performance solutions within their hyperconverged infrastructures (HCI).