I would like to know if there is a way to check how much GPU memory is available before a function uses it. I have code that often uses 1.5 GB of GPU memory or more, and if something else is using the GPU when my program wants to use it, I get a MemoryError
exception or something similar.
I would like to implement some sort of code so that I can check to see if the GPU has enough memory available, and if it does, go ahead and run, but if not, wait until it IS available.
(Preferably, I would like to check before trying to use the GPU rather than using a try-except loop and just retrying if it fails)
I checked the PyOpenCL documentation to see if there was something relevant under device_info, but I couldn't find any actual descriptions.
To monitor the overall GPU resource usage, click the Performance tab, scroll down the left pane, and find the “GPU” option. Here you can watch real-time usage. It displays different graphs for what is happening with your system — like encoding videos or gameplay.
import tensorflow as tf import numpy as np from kmeanstf import KMeansTF print("GPU Available: ", tf. test. is_gpu_available()) nn=1000 dd=250000 print("{:,d} bytes". format(nn*dd*4)) dic = {} for x in "ABCD": dic[x]=tf.
You will need to install nvidia-ml-py3 library in python (pip install nvidia-ml-py3) which provides the bindings to NVIDIA Management library. Here is the code snippet: Thats it!
PyOpenCL lets you access GPUs and other massively parallel compute devices from Python. It tries to offer computing goodness in the spirit of its sister project PyCUDA: Object cleanup tied to lifetime of objects. This idiom, often called RAII in C++, makes it much easier to write correct, leak- and crash-free code.
This is not possible, and is actually a limitation of OpenCL, not just PyOpenCL. See here.
On NVIDIA devices, you can use nvidia-ml-py. Then you can do something like this:
from pynvml import *
nvmlInit()
for i in range(nvmlDeviceGetCount()):
handle = nvmlDeviceGetHandleByIndex(i)
meminfo = nvmlDeviceGetMemoryInfo(handle)
print("%s: %0.1f MB free, %0.1f MB used, %0.1f MB total" % (
nvmlDeviceGetName(handle),
meminfo.free/1024.**2, meminfo.used/1024.**2, meminfo.total/1024.**2))
nvmlShutdown()
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