Supermicro CEO Computex Keynote - 5G Infrastructure Innovation

Super Micro Computer, Inc., a global enterprise computing, storage, networking solutions and green computing technology firm, today announced that it will unveil its Intelligent Edge systems and preview its new CloudDC line of servers designed for large-scale deployments in cloud data centers during a CEO Keynote at COMPUTEXOnline, June 3rd in Taipei.

COMPUTEXOnline Keynote Address:

Supermicro recognized early the need for a robust cloud platform to provide network operators with an environment to develop applications and a distributed edge. This is especially important as core 5G network functions will be tightly interwoven with and fueled by public clouds. Supermicro's next-generation dual-processor CloudDC servers feature multiple storage options in 1U and 2U servers, dual OCP 3.0 compliant AIOM slots for up to four 100GbE ports, support for Open BMC, an all-hybrid backplane design supporting SATA3, SAS3, or NVMe storage drives, and a simplified architecture optimized for hyperscale environments.

"With our already strong position in 5G infrastructure and the initial release of CloudDC servers, Supermicro provides customers with optimized next-generation systems from the edge to the cloud," said Charles Liang, president, and CEO of Supermicro. "This combination demonstrates Supermicro's continuing focus on x86-based systems and support for open-source NFV (network functions virtualization) compliant solutions leveraging NEBS and off-the-shelf validated telco software powered by our server and storage Building Block Solutions®."

Supermicro CloudDC servers offer exceptional value for a multitude of use cases. For the private cloud, CloudDC servers have flexible storage and expansion, NVMe over fabrics, rapid deployment, easy maintenance, and high scalability. In the 5G/telco arena, CloudDC systems are designed to be NEBS Level 3 ready, support O-RAN virtualized network elements such as DU, CU, and core and as well as accommodating FPGA accelerator cards. The platform supports up to four GPU accelerator cards and can process deep learning training and inference, data analytics, graphics, and high-performance computing.