Performance
Intensive
Computing

Design simulation lets designers and engineers create, test and improve designs of real-world airplanes, cars, medical devices and more while working safely and quickly in virtual environments. This workflow also reduces the need for physical tests and allows designers to investigate more alternatives and optimize their products.

The new 4th gen AMD EPYC 8004 family extends the ‘Zen4c’ core architecture into lower-count processors with TDP ranges as low as 80W. The processors are designed especially for edge-server deployments and form factors.

Supermicro’s H13 Petascale Storage Systems is a compact 1U rackmount system powered by the AMD EPYC 97X4 processor (formerly codenamed Bergamo) with up to 128 cores.    

ILM, the visual-effects company founded by George Lucas, is using AMD-powered Supermicro servers and workstations to create the next generation of special effects for movies and TV.

A Taiwanese hospital’s initial use of AI to interpret medical images with consumer graphics cards fell short. The prescription? Supermicro workstations powered by AMD components. 

In a recent test, Supermicro workstations and servers powered by 3rd gen AMD Ryzen Threadripper PRO processors ran engineering simulations nearly as fast as a dual-processor system, but needed only two-thirds as much power.

The Student Cluster Computing challenge made its 16th appearance at the SuperComputer 22 (SC22) event in Dallas. The two student teams that were running AMD EPYC™ CPUs and AMD Instinct™ GPUs were the two teams that aced the Linpack benchmark. That's the test used to determined the TOP500 supercomputers in the world.

Energy company Petrobas, based in Brazil, is using high-performance computing techniques to aid it in its oil and gas exploration, especially in deep-water situations. Petrobas used system integrator Atos to provide more than 250 Supermicro SuperServers. The cluster is ranked 33 on the current top500 list and goes by the name Pegaso.

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.