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 your own GPU cloud is made of several elements, and for example purposes and us being a leading partner of SuperMicro, we will illustrate the building blocks of such a GPU private cloud:
- Hyper-Converged Infrastructure
Compute – 1U Supermicro Ultra
For the compute element of the GPU cloud, we recommend using SuperMicros Ultra SuperServers. We have extensive experience building this out as the compute node. It has 32 DIMM Slots, which can fit up to 8TB DRAM. For the CPU element, it supports Dual Socket P+ (LGA-4189) 3rd Gen Intel® Xeon® Scalable Processors.
Hyper-Converged Infrastructure – 2U 4 Node Supermicro Twin Pro
For the Hyper-Converged Infrastructure, this particular server supports: Dual Socket P+ (LGA-4189) 3rd Generation Intel® Xeon® Scalable Processors, 16 DIMMs which can have up to 4TB RAM. With Intel® X710 Dual port 10GBase-T LAN onboard, the networking element is well equipped to handle many heavy workloads.
Storage – 4U 90 Bay Storage Server
For storage, there is typically a lot of deployment scenarios, this server supports up to 90 bays with the following disk configuration: 90 3.5″/2.5″ Hot-swap SAS3/SATA3 drives, 2x Fixed slim SATA SSD, 2x NVMe M.2 (form factor: 2280 and 22110).
GPU – 4U 8 x H100 GPU Server
This GPU system has NVIDIA® NVLink™ with NVSwitch™ for GPU to GPU interconnect. This server has 8-GPU compatibility to handle all the GPU workloads throughout the cloud.
NVMe – 2U 24 x NVMe Server
For the NVMe element, this server model supports 24x 2.5″ hot-swap NVMe/SATA/SAS drive bays (22x 2.5″ NVMe hybrid) and we’ve found it to be optimally a strong server for these types of configurations.
With all of that considered, you’ll be on your way to building a GPU cloud. Talk to us about building your GPU cloud.
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