SuperMicro continues to push the boundaries in terms of GPU server deployments and form factors. SuperMicro recently announced an 8U GPU, which, in their words, is the “most advanced GPU server, incorporating eight NVIDIA® H100 Tensor Core GPUs”.

Building a GPU cloud contains many variables, hardware and software. You can think of it as building blocks.

Picking the correct GPU Cloud Computing setup is important given the cost and workloads involved when moving to the cloud. We shortlist our recommended building blocks for an optimized GPU cloud.

Building a private GPU cloud can be an extremely hard task and it’s a task that has many components. The first thing to identify is whether you need a fully networked GPU cloud or do your workloads just require an integrated GPU server?

GPU cloud computing is becoming an ever more important part of day-to-day computing life. There are more and more use cases because of the advantages GPUs have over CPUs for particular workloads. We’ve put together a list of GPUs that NVIDIA has here for data center workloads and what they are good for.

Building a GPU cloud can be a timely and expensive experience. There is a mixture of software and hardware you need to put together that makes an optimal GPU cloud.

There are lots of GPU choices depending on your use case and use cases vary wildly. Whether you are a home user gaming or a datacenter trying to machine learn 24/7, the use cases vary. 

There are lots of GPU choices depending on your use case and use cases vary wildly. Whether you are a home user gaming or a datacenter trying to machine learn 24/7, the use cases vary. 

SuperMicro has many solutions available and with such a wide net for building our private cloud deployments, it’s important to put together the right pieces. We’ve teamed up with Supermicro to deliver high-performance hardware solutions that are optimized for on-premise, private cloud infrastructure.

Building out a GPU server can be a daunting and expensive process. With GPU servers becoming more and more popular in data center environments as well as use cases continuing to grow in size, pricing out the right GPU server is important.