Multi-arch DIANA and DIANA-Learn Python Docker images for embedded systems
620
Derek Merck
[email protected]
Rhode Island Hospital and Brown University
Providence, RI
Build multi-arch DIANA and DIANA-Learn Python Docker images for embedded systems.
$ docker run derekmerck/diana:latest
$ docker run derekmerck/diana-learn:latest
This image is based on the [derekmerck/conda][] and derekmerck/keras-tf images, which are, in turn, based on the resin/$ARCH-debian:stretch image. Resin.io base images include a QEMU cross-compiler to facilitate building images for low-power single-board computers on more powerful Intel-architecture desktops and servers.
docker-compose.yml contains build descriptions for all relevant architectures.
amd64$ docker-compose build diana-amd64 diana-learn-amd64
Desktop computers/vms, UP boards, and the Intel NUC are amd64 devices. The appropriate image can be built and pushed from Travis CI.
arm32v7Most low-power single board computers such as the Raspberry Pi and Beagleboard are arm32v7 devices. Appropriate images can be cross-compiled and pushed from Travis CI.
$ docker-compose build diana-arm32v7 diana-learn-arm32v7
arm64v8The NVIDIA Jetson TX2 uses a Tegra arm64v8 cpu. The appropriate image can be built natively and pushed from Packet.io, using a brief tenancy on a bare-metal Cavium ThunderX ARMv8 server.
$ apt update && apt upgrade
$ curl -fsSL get.docker.com -o get-docker.sh
$ sh get-docker.sh
$ docker run hello-world
$ apt install git python-pip
$ pip install docker-compose
$ git clone http://github.com/derekmerck/diana-xarch
$ cd diana-xarch
$ docker-compose build diana-arm64v8 diana-learn-arm64v8
Although Resin uses Packet ARM servers to compile arm32 images, the available ThunderX does not implement the arm32 instruction set, so it cannot compile natively for the Raspberry Pi.
After building new images, call manifest-it.py to push updated images and build the Docker
multi-architecture service mappings.
$ python3 manifest-it diana-xarch.manifest.yml
MIT
Content type
Image
Digest
Size
553 MB
Last updated
almost 8 years ago
docker pull derekmerck/diana-learn