Performance Intensive Computing

This is the third in a four-part series on blockchain’s many facets, including being the primary pillar of the emerging Web3.

This is the second in a four-part series on blockchain’s many facets, including being the primary pillar of the emerging Web3.

This is the first story in a four-part series on blockchain’s many facets, including being the primary pillar of the emerging Web3. 

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.