Docker Containers

We have tested our docker images for CentOS >= 7.4 and Ubuntu >= 16.04. We currently have docker images for NVIDIA GPUs, and Intel Integrated GPUs, Intel CPUs and Intel FPGAs using OpenJDK 11, 17 and GraalVM 22.2.0:

  • TornadoVM docker images for NVIDIA GPUs

  • TornadoVM docker images for Intel Integrated Graphics, Intel FPGAs, and Intel CPUs

Nvidia GPUs

Prerequisites

The tornadovm-nvidia-openjdk docker image needs the docker nvidia daemon. More info here: https://github.com/NVIDIA/nvidia-docker.

How to run?

  1. Pull the image

For the tornadovm-nvidia-openjdk image:

$ docker pull beehivelab/tornadovm-nvidia-openjdk:latest

This image uses the latest TornadoVM for NVIDIA GPUs and OpenJDK 17.

  1. Run an experiment

We provide a runner script that compiles and run your Java programs with Tornado. Here’s an example:

$ git clone https://github.com/beehive-lab/docker-tornado
$ cd docker-tornado

## Run Matrix Multiplication - provided in the docker-tornado repository
$ ./run_nvidia_openjdk.sh tornado -cp example/target/example-1.0-SNAPSHOT.jar example.MatrixMultiplication

Computing MxM of 2048x2048
    CPU Execution: 0.36 GFlops, Total time = 48254 ms
    GPU Execution: 277.09 GFlops, Total Time = 62 ms
    Speedup: 778x

Using TornadoVM with GraalVM for NVIDIA GPUs

With JDK 17:

$ docker pull beehivelab/tornadovm-nvidia-graalvm:latest

Some options

# To see the generated OpenCL kernel
$ ./run_nvidia.sh tornado --printKernel example/MatrixMultiplication

# To check some runtime info about the kernel execution and device
$ ./run_nvidia.sh tornado --debug example/MatrixMultiplication

The tornado command is just an alias to the java command with all the parameters for TornadoVM execution. So you can pass any Java (OpenJDK or Hotspot) parameter.

$ ./run_nvidia.sh tornado --jvm="-Xmx16g -Xms16g" example/MatrixMultiplication

Intel Integrated Graphics

Prerequisites

The beehivelab/tornadovm-intel-openjdk docker image Intel OpenCL driver for the integrated GPU installed. More info here: https://github.com/intel/compute-runtime.

How to run?

  1. Pull the image

For the beehivelab/tornadovm-intel-openjdk image:

$ docker pull beehivelab/tornadovm-intel-openjdk:latest

This image uses the latest TornadoVM for Intel integrated graphics and OpenJDK 17.

  1. Run an experiment

We provide a runner script that compiles and run your Java programs with TornadoVM. Here’s an example:

$ git clone https://github.com/beehive-lab/docker-tornado
$ cd docker-tornado

## Run Matrix Multiplication - provided in the docker-tornado repository
$ ./run_intel_openjdk.sh tornado -cp example/target/example-1.0-SNAPSHOT.jar example.MatrixMultiplication --parms="256"

Computing MxM of 256x256
    CPU Execution: 1.53 GFlops, Total time = 22 ms
    GPU Execution: 8.39 GFlops, Total Time = 4 ms
    Speedup: 5x

Using TornadoVM with GraalVM for Intel Integrated Graphics

With JDK 17:

$ docker pull beehivelab/tornadovm-intel-graalvm:latest