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NOTE: is the better way of doing this these days.

Compile & Run a test script on a GPU-enabled Ubuntu Docker container

This needs to run on a GPU-enabled machine. Here's how to set one up on AWS:

Quick start: run on an Ubuntu AMI with CUDA 6.5 built by this guy:

  • AMI: ami-2cbf3e44
  • Instance type: g2.2xlarge

Then get into the AMI and do this:

# Run this command which somehow makes the nvidia devices show up under /dev/:

# Install docker:
curl -sSL | sudo sh

# Pull down the GPU test image:
sudo docker pull nricklin/ubuntu-gpu-test

# Run the test:
DOCKER_NVIDIA_DEVICES="--device /dev/nvidia0:/dev/nvidia0 --device /dev/nvidiactl:/dev/nvidiactl --device /dev/nvidia-uvm:/dev/nvidia-uvm"
sudo docker run $DOCKER_NVIDIA_DEVICES nricklin/ubuntu-gpu-test

And here is the result if successful:

Number of CUDA Devices = 1
Device 0 has name GRID K520 with compute capability 3.0 canMapHostMemory=1
                           global memory = 3.9998
HostToDevice PCI Express BW=9.56939 GB/s
DeviceToHost PCI Express BW=8.86773 GB/s
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