I have deployed Llama 3.1 70B and Llama 3.1 8B on my system and it works perfectly for the 8B model. When I tested it for 70B, it underutilized the GPU and took a lot of time to respond. Here…
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…
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'm trying to train a model with Yolov8. Everything was good but today I suddenly notice getting this warning apparently related to PyTorch and cuDNN. In spite the warning, the training seems to be progressing though. I'm not sure if…
My VS Code suddenly started crashing within 1sec of starting up. VS Code Version: 1.90.0 OS Version: Ubuntu 22.04 Running code --disable-gpu --disable-extensions --verbose I've tried: Reinstalling VSCode (using snap) Run code Run code --disable-gpu --disable-extensions Run code --disable-gpu --disable-software-rasterizer…
I am trying to install TensorFlow on Ubuntu/VSCode and I get these error message and can't the problem. Here are the error message: (.venv) user:~/Desktop/Code$ python3 -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))" 2024-05-10 15:36:48.869402: I tensorflow/core/util/port.cc:113] oneDNN custom operations are…
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 installed oneAPI base kit and HPC kit (2024.0) on public cluster to test the performance of gemm. but I got segmentation fault error. I don't know how to fix this problem. I used offline installer and installed it locally.…
I would like to flatten a docker image by using docker multi-stage. My Dockerfile is something like this: FROM nvcr.io/nvidia/l4t-tensorrt:r8.2.1-runtime as build # ... FROM scratch COPY --from=build / / CMD ["/bin/bash"] However if I try to run this image…
I made a fresh install of docker desktop from official docs docker desktop. Then I installed NVIDIA Container Toolkit following official docs nvidia container toolkit. When I run docker with non-root permission: docker run --rm --gpus all nvidia/cuda:11.6.2-base-ubuntu20.04 nvidia-smi It…