Is these processes are computed parallelly using MPS?

We enabled MPS and tyied to run “process A” and “process B” parallelly.
However, performance didn’t seem to be improved.

Did we run “process A” and “process B” simultaneously when nvidia-smi command output like below?

・Output of nvidia-smi
±---------------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|==================================================================================|
| 0 XXXX C nvidia-cuda-mps-server XXXMiB |
| 0 YYYY M+C process A YYYMiB |
| 0 ZZZZ M+C process B ZZZMiB |
±----------------------------------------------------------------------------------+

・Environment

  • GPU
    Single Nvidia T4 GPU

  • How to enable MPS server
    export CUDA_VISIBLE_DEVICES=0
    sudo nvidia-smi -i 0 -c EXCLUSIVE_PROCESS
    sudo nvidia-cuda-mps-control -d
    unset CUDA_VISIBLE_DEVICES

  • How to start process A and B(using nvidia-docker2)
    docker create -e NVIDIA_VISIBLE_DEVICES=0 --runtime=nvidia --ipc=host --name proca imageforproca
    docker run foo(started process A)
    docker create -e NVIDIA_VISIBLE_DEVICES=0 --runtime=nvidia --ipc=host --name procb imageforprocb
    docker run foo(started process B)

Hi shota.takano,

May I know what’s the platform you’re using?

We tested our program on x86_64 server on prem.
Other specs are below.

[specs]
nvidia driver:410.104
cuda:10.0

Hi shota.takano,

Sorry for the late reply, for Video Codec SDK issue, please file into relevant forum: https://devtalk.nvidia.com/default/board/244/video-codec-and-optical-flow-sdk/