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Add Docker support #18

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34 changes: 34 additions & 0 deletions Dockerfile
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FROM ubuntu:20.04

# Install dependencies
# DEBIAN_FRONTEND=noninteractive necessary for tzdata dependency package
RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y \
clang \
cmake \
libboost-all-dev \
libprotobuf-dev \
protobuf-compiler \
git \
pip
RUN update-alternatives --install /usr/bin/cc cc /usr/bin/clang 100 && \
update-alternatives --install /usr/bin/c++ c++ /usr/bin/clang++ 100

# Install SEAL
WORKDIR /home/root
RUN git clone -b v3.6.4 https://github.com/microsoft/SEAL.git && \
cd SEAL && \
cmake -DSEAL_THROW_ON_TRANSPARENT_CIPHERTEXT=OFF . && \
make -j && \
make install

# Install EVA
WORKDIR /home/root
RUN git clone -b v1.0.1 https://github.com/microsoft/EVA && \
cd EVA && \
git submodule update --init && \
cmake . && \
make -j && \
python3 -m pip install -e python && \
python3 python/setup.py bdist_wheel --dist-dir='.' && \
python3 -m pip install numpy && \
python3 tests/all.py
20 changes: 20 additions & 0 deletions README.md
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Expand Up @@ -11,6 +11,8 @@ EVA targets [Microsoft SEAL](https://github.com/microsoft/SEAL) — the industry

EVA is a native library written in C++17 with bindings for Python. Both Linux and Windows are supported. The instructions below show how to get started with EVA on Ubuntu. For building on Windows [EVA's Azure Pipelines script](azure-pipelines.yml) is a useful reference.

You can also build a Docker image with EVA and SEAL installed. This is useful if you want to run EVA on unsupported platforms (e.g. macOS). See [Getting Started with Docker](#getting-started-with-docker) below.

### Installing Dependencies

To install dependencies on Ubuntu 20.04:
Expand Down Expand Up @@ -68,6 +70,24 @@ python3 image_processing.py
This will compile and run homomorphic evaluations of a Sobel edge detection filter and a Harris corner detection filter on `examples/baboon.png`, producing results of homomorphic evaluation in `*_encrypted.png` and reference results from normal execution in `*_reference.png`.
The script also reports the mean squared error between these for each filter.

## Getting Started with Docker

Build the Docker image:

```bash
docker build -t eva:v1.0.1 .
```

Run the Docker image:

```bash
docker run -ti eva:v1.0.1
```

This will drop you into the running Docker container where you will find a working installation of SEAL and EVA.

> For installing Docker, follow the instructions [here](https://docs.docker.com/get-docker/).

## Programming with PyEVA

PyEVA is a thin Python-embedded DSL for producing EVA programs.
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