Performance
Intensive
Computing

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.

CPU chipsets are not normally considered systems-on-chip (SoC) but the fourth generation of AMD EPYC processors incorporate numerous I/O functionality at a high level of integration.

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..

AMD’s announcement of its fourth generation EPYC 9004 Series processors includes major advances in how these chipsets are designed and produced. Part 2 of 4.

AMD announces its fourth-generation EPYC™ CPUs. The new EPYC 9004 Series processors demonstrate advances in hybrid, multi-die architecture by decoupling core and I/O processes. Part 1 of 4.

Join Supermicro online Nov. 10th to watch the unveiling of the company’s new A+ systems -- featuring next-generation AMD EPYC™ processors. They can't tell us any more right now. But you can register for a link to the event by scrolling down and signing-up on this page.

Weka’s file system, WekaFS, unifies your entire data lake into a shared global namespace where you can more easily access and manage trillions of files stored in multiple locations from one directory.

Running heavy AI/ML workloads can be a challenge for any server, but the SuperBlade has extremely fast networking options, upgradability, the ability to run two AMD EPYC™ 7000-series 64-core processors and the Horovod open-source framework for scaling deep-learning training across multiple GPUs.