Building a GPU cluster requires specific hardware to ensure efficient and reliable operations. To help you decide wisely, we’ve put together a list of recommended hardware configurations that will maximize the efficiency of your GPU cluster.
Processor for GPU Cluster
For your GPU cluster to operate and coordinate, a powerful CPU is also required. We advise using Intel Xeon processors, Because they have the strength required to run substantial, data-intensive applications.
Which GPU should you use in GPU Cluster?
GPUs like the NVIDIA Tesla, AMD Radeon Instinct, or Intel Xeon Phi are good choices because they have strong processing power and efficient memory. Depending on your workload and the size of your dataset, you will need a certain number of GPUs for your cluster
RAM Requirements in a GPU Cluster
Large datasets need lots of RAM because data transfer between the CPU and GPUs must be seamless. We suggest a minimum of 64GB of RAM for a GPU cluster.
Network Interface for GPU Cluster
Because it enables prompt and efficient communication between nodes, a GPU cluster’s network interface is crucial. You should choose a network interface with low latency and fast data transfer rates, such as Infiniband or 40/100 Gb Ethernet.
What kind of Storage for a GPU Cluster?
In order to store and access large datasets, storage is also an essential part of a GPU cluster. We advise using quick and dependable storage, such as NVMe SSDs or RAID setups.
PSU selection for GPU Cluster
Running a GPU cluster requires the presence of a power supply. We advise using a power supply that has multiple 8-pin power connectors for the GPUs and is rated for at least 1000W.
How to Cool a GPU Cluster?
GPU clusters generate a lot of heat, so effective cooling is necessary to prevent overheating and guarantee the durability of the hardware. You can use liquid cooling or air cooling, depending on your preferences and budget.
When deciding which hardware specifications to use, building a GPU cluster can be challenging. But why go through all this hassle when you can leave it to the experts?
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