How can I flush GPU memory using CUDA physical reset is unavailable

Question

My CUDA program crashed during execution  before memory was flushed  As a result  device memory remained occupied   I m running on a GTX 580  for which nvidia-smi --gpu-reset is not supported   Placing cudaDeviceReset   in the beginning of the program is only affecting the current context created by the process and doesn t flush the memory allocated before it   I m accessing a Fedora server with that GPU remotely  so physical reset is quite complicated    So  the question is - Is there any way to flush the device memory in this situation

User · Accepted Answer

Although it should be unecessary to do this in anything other than exceptional circumstances, the recommended way to do this on linux hosts is to unload the nvidia driver by doing

$ rmmod nvidia

with suitable root privileges and then reloading it with

$ modprobe nvidia

If the machine is running X11, you will need to stop this manually beforehand, and restart it afterwards. The driver intialisation processes should eliminate any prior state on the device.

This answer has been assembled from comments and posted as a community wiki to get this question off the unanswered list for the CUDA tag

User · Answer

on macOS    OS X   if someone else is having trouble with the OS apparently leaking memory    https   github com phvu cuda-smi is useful for quickly checking free memory Quitting applications seems to free the memory they use  Quit everything you don t need  or quit applications one-by-one to see how much memory they used  If that doesn t cut it  quitting about 10 applications freed about 500MB   15  for me   the biggest consumer by far is WindowServer  You can Force quit it  which will also kill all applications you have running and log you out  But it s a bit faster than a restart and got me back to 90  free memory on the cuda device

User · Answer

for the ones using python   import torch  gc gc collect   torch cuda empty cache

User · Answer

One can also use nvtop  which gives an interface very similar to htop  but showing your GPU s  usage instead  with a nice graph  You can also kill processes directly from here   Here is a link to its Github   https   github com Syllo nvtop  NVTOP interface

User · Answer

First type   nvidia-smi   then select the PID that you want to kill  sudo kill -9 PID

User · Answer

check what is using your GPU memory with  sudo fuser -v  dev nvidia    Your output will look something like this                        USER        PID  ACCESS COMMAND  dev nvidia0         root       1256  F   m  Xorg                      username   2057  F   m  compiz                      username   2759  F   m  chrome                      username   2777  F   m  chrome                      username   20450 F   m  python                      username   20699 F   m  python   Then kill the PID that you no longer need on htop or with  sudo kill -9 PID    In the example above  Pycharm was eating a lot of memory so I killed 20450 and 20699

User · Answer

I also had the same problem  and I saw a good solution in quora  using   sudo kill -9 PID    see https   www quora com How-do-I-kill-all-the-computer-processes-shown-in-nvidia-smi

[cuda] How can I flush GPU memory using CUDA (physical reset is unavailable)

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