I'm trying to get Tensorflow working on my Ubuntu 24.04.1 with a GPU. According to this page: Docker is the easiest way to run TensorFlow on a GPU since the host machine only requires the NVIDIA® driver So I'm trying…
I have a dockerized flask application. I wish to run the following code as multiprocessing but right now it is utilizing CPU cores and the container is crashing. What should be done to make sure it utilizes the GPU instead…
I have installed Nvidia's GPU operator and have my GPU-enabled node automatically labelled (what I treat as important, long list of other labels is there as well): nvidia.com/gpu.count=1 Node is seemingly schedule able Conditions: Type Status LastHeartbeatTime LastTransitionTime Reason Message…
i use requestAnimationFrame in a js webgl project where i change the pixel color from black to white on each frame by accessing a texture that contains the content of the last frame ) but the framerate exceeds the Hz…
Background I have spent the past week doing experiments towards using GPU for audio processing/synthesis, for example in areas like finite difference modeling (eg. wave equation) where the equations are highly parallelized at least at each serial time step. However,…
For some reason, any docker container with CUDA cannot see my GPU. When I run this: docker run --gpus=all --rm nvcr.io/nvidia/k8s/cuda-sample:nbody nbody -gpu -benchmark I have this output: ... Error: only 0 Devices available, 1 requested. Exiting. The CUDA container…
I bought a new laptop and installed VS Code and Tensorflow on Windows. The TF Python script needs a conda virtual environment that can access Nvidia GPU card. I got the virtual environment working fine. I also got the TF…
I installed the docker engine by exactly following the instructions (using the repository) on the docker website (I'm on Debian 11) without skipping any steps. I can definitely run the docker hello world. I tried to install Docker desktop but…
I stragle to make a Batch process to run with GPU in AWS Batch. I set Compute environment: - Type: Managed - Prov. model: EC2 - Instance type: g4dn.xlarge - Status: Valid - State: Enabled - Min CPU: - -…
I'm running pytorch on an ubuntu server 18.04 LTS. I have an nvidia gpu with 8 GB or ram. I'd like to experiment with the new llma2-70B-chat model. I'm trying to use peft and bitsandbytes to reduce the hardware requirements…