Since vSphere Bitfusion 4.0, you can use CLI command arguments to filter the GPUs in your resource pool and start your applications on a specific set of GPUs.

You can use a --filter argument with the run, request_gpus, and list_gpus commands and run the commands with a specific set of GPUs or servers. You can also combine filters to list servers and GPUs that satisfy multiple conditions. For each data type, you must use an appropriate operator, such as <, >, >=, <=, =, or !=.

Table 1. List of Available GPU and Server Filters
Filter Data Type Description
device.index Integer The system index of a GPU. For example, 1. To see the indices of your GPUs, run the nvidia-smi command.
device.name String The model name of a GPU device. For example, NVIDIA Tesla T4.
device.memory Integer The physical memory size of a GPU device in MB. For example, enter 16384 for a GPU device with 16 GB memory size.
device.capability Version The NVIDIA device CUDA compute capability. The CUDA compute capability is a mechanism that NVIDIA uses with the CUDA API to specify the features that your GPUs support. The value must be entered in a X.Y format. For example, 8.0. For more information, see the NVIDIA CUDA GPUs documentation.
server.addr String The IP address of a vSphere Bitfusion server.
server.hostname String The hostname of a vSphere Bitfusion server.
server.has-rdma Boolean The vSphere Bitfusion server uses an RDMA network connection.
server.cuda-version Version The CUDA version that is installed on a vSphere Bitfusion server. The value must be entered in a X.Y format. For example, 11.3.
server.driver-version Version The NVIDIA driver version that is installed on a vSphere Bitfusion server. The value must be entered in a X, X.Y, or X.Y.Z format. For example, 460.73.
For example, to list your GPUs devices with memory size greater than 16 GB, run the bitfusion list_gpus --filter "device.memory>16384" command.
For example, to run an AI or ML workload on GPUs devices with Ampere GPU microarchitecture only, run the bitfusion run -n 1 --filter "device.capability=8.0" -- workload command. Similarly, to run the workload on GPUs devices with Volta GPU microarchitecture only, run the bitfusion run -n 1 --filter "device.capability=7.0" -- workload command.
Note: GPUs devices with Ampere GPU microarchitecture have CUDA compute capability equal to CUDA version 8.0 and GPUs devices with Volta GPU microarchitecture have CUDA compute capability equal to CUDA version 7.0. For more information, see the NVIDIA CUDA GPUs documentation.