Have you tried adding robustness support to your OpenGL implementation using GL_ARB_robustness? 2.6 “Graphics Reset Recovery” Certain events can result in a reset of the GL context. Such a reset causes all context state to be lost. Recovery from such events requires recreation of all objects in the affected context. The current status of the … Read more
Set the environment variable CUDA_DEVICE_ORDER as: export CUDA_DEVICE_ORDER=PCI_BUS_ID Then the GPU IDs will be ordered by pci bus IDs.
The accepted answer doesn’t work for me, probably because nvidia-smi has different formats across different versions/hardware. I’m using a much cleaner command: nvidia-smi | grep ‘python’ | awk ‘{ print $3 }’ | xargs -n1 kill -9 You can replace $3 in the awk expression to fit your nvidia-smi output. It is the n-th column … Read more
Update (Sep. 17, 2017): NVIDIA recently published an article detailing how to use OpenGL on headless systems, which is a very similar use case as the question describes. In summary: Link to libOpenGL.so and libEGL.so instead of libGL.so. (Your linker options should therefore be -lOpenGL -lEGL Call eglGetDisplay, then eglInitialize to initialize EGL. Call eglChooseConfig … Read more
No. It means you have called a CUDA kernel with one block and that one block has 100 active threads. You’re passing size as the second function parameter to your kernel. In your kernel each of those 100 threads executes the for loop 100 times. #pragma unroll is a compiler optimization that can, for example, … Read more
To check which devices are available to TensorFlow you can use this and see if the GPU cards are available: from tensorflow.python.client import device_lib print(device_lib.list_local_devices()) Edit Also, you should see this kind of logs if you use TensorFlow Cuda version : I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcublas.so.*.* locally I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library … Read more
CUDA activity from independent host processes will normally create independent CUDA contexts, one for each process. Thus, the CUDA activity launched from separate host processes will take place in separate CUDA contexts, on the same device. CUDA activity in separate contexts will be serialized. The GPU will execute the activity from one process, and when … Read more
For those whose problem has not been solved; try this solution: Set the global environment variable “J2D_D3D” to “false” inside the OS. According to Sun, this setting is used to turn off the Java 2D system’s use of Direct3D in Java 1.4.1_02 and later. ie: simply create a environmental variable with name “J2D_D3D” and value … Read more
Now only Tesla V100 and Titan V have tensor cores. Both GPUs have 5120 cuda cores where each core can perform up to 1 single precision multiply-accumulate operation (e.g. in fp32: x += y * z) per 1 GPU clock (e.g. Tesla V100 PCIe frequency is 1.38Gz). Each tensor core perform operations on small matrices … Read more
You will need to add the folder containing the “cl.exe” file to your path environment variable. For example: C:\Program Files\Microsoft Visual Studio 10.0\VC\bin Edit: Ok, go to My Computer -> Properties -> Advanced System Settings -> Environment Variables. Here look for “PATH” in the list, and add the path above (or whatever is the location … Read more