Difference between revisions of "GPUs in Red Cloud"
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Red Cloud supports GPU computing and has two different GPU instance flavors that allow for GPU computing. In order to use a GPU in Red Cloud, you will need to select a flavor of machine with a GPU. Currently Red Cloud instances feature '''[https://www.nvidia.com/en-us/data-center/tesla-t4/ Nvidia Tesla T4]''' and '''[https://www.nvidia.com/en-us/data-center/tesla-v100/ Nvidia Tesla V100]''' GPU accelerators in these flavors: | Red Cloud supports GPU computing and has two different GPU instance flavors that allow for GPU computing. In order to use a GPU in Red Cloud, you will need to select a flavor of machine with a GPU. Currently Red Cloud instances feature '''[https://www.nvidia.com/en-us/data-center/tesla-t4/ Nvidia Tesla T4]''' and '''[https://www.nvidia.com/en-us/data-center/tesla-v100/ Nvidia Tesla V100]''' GPU accelerators in these flavors: | ||
Revision as of 11:37, 9 July 2020
(This page under development)
Red Cloud supports GPU computing and has two different GPU instance flavors that allow for GPU computing. In order to use a GPU in Red Cloud, you will need to select a flavor of machine with a GPU. Currently Red Cloud instances feature Nvidia Tesla T4 and Nvidia Tesla V100 GPU accelerators in these flavors:
Flavor | CPUs | GPUs | RAM |
---|---|---|---|
*c4.t1.m20 | 4 | 1 Nvidia Tesla T4 | 20 GB |
*c14.g1.m60 | 14 | 1 Nvidia Tesla V100 | 60 GB |
When launching an instance, you can use either the base Linux or Windows instances and install your own GPU libraries, or select CUDA source images such as (...), select a GPU-enabled flavor, and configure the instance as you would any other instance.
Once your instance is launched, you will have access to the GPU within the VM and can install software (pytorch, tensorflow) that will use the GPU.