Nvidia rendering on Docker

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• How to add fonts to docker image

  I'm using node node:15-slim for building nodejs image. Apparently this image doesn't have any fonts included. So Fontconfig error: Cannot load default config file: No such file: (null) appears. I added .fonts/Ubuntu-Light.ttf into my project and tried to copy that file in Dockerfile

  FROM node:15-slim
  COPY .fonts .fonts/ <-- Here I copy 
  WORKDIR /app
  COPY package*.json /app/
  RUN npm install
  COPY src/* /app/src/
  COPY tsconfig.json /app/
  RUN npm run build
  

  But it doesn't help. I don't want to use not slim version and hoping to find solution Thanks in advance!
• What does 'ADD file ... in /' in docker base images at dockerhub.com

  I'm trying to find a suitable base image at Dockerhub, and I'm not sure whether the image with the tag Nvidia/cuda:11.1.1-base-ubuntu20.04 contains the ubuntu20.04 environment or not. If the answer is yes, why don't I see anything about ubuntu in its Dockerfile. And what's the use of ADD file ...
• Is there any way to solve inaccessible jarfile ords.war error?

  I tried creating ORDS docker image.

  It stops when on the line
  RUN echo "" && chmod +x /tmpdocker-run.sh && /tmp/docker-run.sh
  with exit code:1.

  The error message is: Error:Uable to access jarfile ords.war.

  I have already installed apex on docker and I am not able to install ORDS now.
• Differences between rigid and smooth skinning

  In computer graphics,

  how do we compute the displacement of a vertex in smooth skinning using a weight function W and displacement from the affecting joint to vertex d_i??
• Questions about Computer graphics?

  I have questions about computer graphics course, Are they true or not?

  1-In character animation, obtaining joint angels from giving coordinates is done by forward kinematics

  2-Orthographic projection projects all the pointa in the world along parallel lines onto the image plane

  3-Raytracing produces viewer-independent lighting solutions.
• python how to delete an oval in a list

  Hi I started python like 1 month ago and there is a thing that I can't resolve in my program.

  I'm making a little game like space invaders but the "oval21" does not disappear when oval21set.vie == 0 I need help please!!!

  elif event.char == "p":
  id_liste.append(cnv.create_line(projectile_trajectoire,550,projectile_trajectoire,0, fill="red", width="3"))
  if projectile_trajectoire in range(60,130):
      if oval21Set.vie > 0:
          oval21Set.vie -= 1
          if oval21Set.vie < 1:
              oval21 = oval_list[2]
              delete_oval(oval21)
  
• "Out of memory" in hibrid MPI/OpenMP for GPU acceleration

  I have compiled Quantum ESPRESSO (Program PWSCF v.6.7MaX) for GPU acceleration (hibrid MPI/OpenMP) with the next options:

  module load compiler/intel/2020.1
  module load hpc_sdk/20.9
  
  ./configure F90=pgf90 CC=pgcc MPIF90=mpif90 --with-cuda=yes --enable-cuda-env-check=no --with-cuda-runtime=11.0 --with-cuda-cc=70 --enable-openmp BLAS_LIBS='-lmkl_intel_lp64 -lmkl_intel_thread -lmkl_core'
  
  make -j8 pw
  

  Apparently, the compilation ends succesfully. Then, I execute the program:

  export OMP_NUM_THREADS=1
  mpirun -n 2 /home/my_user/q-e-gpu-qe-gpu-6.7/bin/pw.x < silverslab32.in > silver4.out
  

  Then, the program starts running and print out the next info:

  Parallel version (MPI & OpenMP), running on       8 processor cores
  Number of MPI processes:                 2
  Threads/MPI process:                     4
  ...
  GPU acceleration is ACTIVE
  ...
  Estimated max dynamical RAM per process >      13.87 GB
  Estimated total dynamical RAM >      27.75 GB
  

  But after 2 minutes of execution the job ends with error:

  0: ALLOCATE: 4345479360 bytes requested; status = 2(out of memory)
  0: ALLOCATE: 4345482096 bytes requested; status = 2(out of memory)
  --------------------------------------------------------------------------
  Primary job  terminated normally, but 1 process returned
  a non-zero exit code. Per user-direction, the job has been aborted.
  --------------------------------------------------------------------------
  --------------------------------------------------------------------------
  mpirun detected that one or more processes exited with non-zero status, thus causing
  the job to be terminated. The first process to do so was:
  
    Process name: [[47946,1],1]
    Exit code:    127
  --------------------------------------------------------------------------
  

  This node has > 180GB of available RAM. I check the Memory use with the top command:

     PID USER      PR  NI    VIRT    RES    SHR S  %CPU %MEM     TIME+ COMMAND
   89681 my_user   20   0   30.1g   3.6g   2.1g R 100.0  1.9   1:39.45 pw.x
   89682 my_user   20   0   29.8g   3.2g   2.0g R 100.0  1.7   1:39.30 pw.x
  

  I noticed that the process stops when RES memory reaches 4GB. This are the caracteristics of the node:

  (base) [my_user@gpu001]$ numactl --hardware
  available: 2 nodes (0-1)
  node 0 cpus: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 28 29 30 31 32 33 34 35 36 37 38 39 40 41
  node 0 size: 95313 MB
  node 0 free: 41972 MB
  node 1 cpus: 14 15 16 17 18 19 20 21 22 23 24 25 26 27 42 43 44 45 46 47 48 49 50 51 52 53 54 55
  node 1 size: 96746 MB
  node 1 free: 70751 MB
  node distances:
  node   0   1
    0:  10  21
    1:  21  10
  
  (base) [my_user@gpu001]$ free -lm
                total        used        free      shared  buff/cache   available
  Mem:         192059        2561      112716         260       76781      188505
  Low:         192059       79342      112716
  High:             0           0           0
  Swap:          8191           0        8191
  

  The version of MPI is: mpirun (Open MPI) 3.1.5

  This node is a compute node in a cluster, but no matter if I submit the job with SLURM or run it directly on the node, the error is the same. Note that I compile it on the login node and run it on this GPU node, the difference is that on the login node it has no GPU connected.

  I would really appreciate it if you could help me figure out what could be going on. Thank you in advance!
• How to disable GPUs in H2O AutoML

  When I run an experiment with H2O AutoML, I got the error: "terminate called after throwing an instance of 'thrust::system::system_error' what(): parallel_for failed: invalid resource handle". This error message comes from XGBoost and it is because of the GPU limit exceed.

  While I'm using the regular XGBoost, I set the cuda visible devices parameter to blank to disable GPUs. However, this arguments seems to be ignored in H2O AutoML - XGBoost implementation.

  import os
  os.environ["CUDA_VISIBLE_DEVICES"] = ""
  

  Currently, the only xgboost can be run on gpu in H2O AutoML.

  The question it that anybody knows how to disable GPUs in H2O AutoML?

  As a workaround, I excluded XGBoost algorithm to run my experiment for now. The trouble is passed when I exclude XGBoost but I do not want to give up the power of XGBoost.

  from h2o.automl import H2OAutoML
  model = H2OAutoML(max_runtime_secs = 60*60*2, exclude_algos = ["XGBoost"])
  
• Is there a good GPU prime number finding program

  I was looking around and could not find a good GPU based prime number finder. I have found many easy to use CPU based programs but not very many GPU. It may be just me but the instructions are a bit convoluted for the ones I have found.
• Can GPUs be logically integrated?

  Is there any way to virtualize or set up physical 4 GPUs logically grouped into 1 GPU?

  The objective is to consolidate the vRAM of 4 GPUs and write them like 1 GPU with greater availability.

  In the case of deep-learning, I am aware of the parts that deal with data parallel.

  I was wondering if there was a case or a way that the GPU of the OS kernel itself was integrated logically in advance.
• Why Nvidia's GPU is only used for training purpose?

  I have seen and observe that Nvidia's GPU is only used for machine learning. Like (The cores of Machine Learning uses Cuda Cores) but why not AMD radeon are used for machine learning (if stream processors can be directly used in Machine Learning by using openCL) ?
• NVIDIA driver v461.09 : Process gets stuck

  I have installed the above version for NVIDIA drivers and it seems that the process gets stuck and the GPU shows 100 percent usage although there is no activity.

  Does anybody know any troubleshooting which can be done to help find out what causes this as the previous version 457.09 has no problems.

  Has something changed?