Is It Unsafe To Run Multiple Tensorflow Processes On The Same Gpu?

I only have one GPU (Titan X Pascal, 12 GB VRAM) and I would like to train multiple models, in parallel, on the same GPU. I tried encapsulated my model in a single python program (

Solution 1:

In short: yes it is safe to run multiple procceses on the same GPU (as of May 2017). It was previously unsafe to do so.

Link to tensorflow source code that confirms this

Solution 2:

Answer

Depending on video memory size, it will be allowed or not.

For my case I have total video memory of 2GBs while the single instance reserves about 1.4GB. When I have tried to run another tensorflow code while I was running already the speech recognition training.

2018-08-28 08:52:51.279676:IT:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1405]Found device 0 with properties:name: GeForce 940MX major: 5 minor:0memoryClockRate(GHz):1.2415pciBusID:0000:01:00.0totalMemory: 2.00GiB freeMemory:1.65GiB2018-08-28 08:52:51.294948:IT:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1484]Adding visible gpu devices:02018-08-28 08:52:55.643813:IT:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:965]Device interconnect StreamExecutor with strength 1 edge matrix:2018-08-28 08:52:55.647912:IT:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:971]02018-08-28 08:52:55.651054:IT:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:984]0:N2018-08-28 08:52:55.656853:IT:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1097]CreatedTensorFlowdevice(/job:localhost/replica:0/task:0/device:GPU:0with1409 MBmemory)->physicalGPU(device:0,name:GeForce940MX,pci bus id:0000:01:00.0,computecapability:5.0)

I got the following error in speech recogntion, which completely terminated the script: (I think according to this is related to out of video memory)

2018-08-2808:53:05.154711: ET:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:1108] could not synchronize on CUDA context: CUDA_ERROR_LAUNCH_FAILED ::
Traceback (most recent call last):
  File"C:\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1278, in _do_call
    return fn(*args)
  File"C:\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1263, in _run_fn
    options, feed_dict, fetch_list, target_list, run_metadata)
  File"C:\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1350, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.InternalError: GPU sync failed