0.1.13

Dockerfile

@@ -1,12 +1,23 @@
-FROM ubuntu:latest
-
+#FROM nvidia/cuda:11.3.0-devel-ubuntu20.04
+FROM nvidia/cuda:11.0-base
 RUN apt-get update && \
     apt-get install -y --no-install-recommends -y \
     python3.8 python3-pip python3.8-dev
-
-RUN pip install virtualenv
-RUN virtualenv --python=python3.8 venv
-RUN venv/bin/pip install py-entangle
-ENV PATH="venv/bin/:${PATH}"
 
+RUN apt install -y wget 
+RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
+RUN mkdir /root/.conda 
+RUN bash Miniconda3-latest-Linux-x86_64.sh -b
+RUN rm -f Miniconda3-latest-Linux-x86_64.sh 
+
+#RUN pip install virtualenv
+#UN virtualenv --python=python3.8 venv
+#RUN venv/bin/pip install py-entangle
+#RUN venv/bin/pip install numba
+ENV PATH="/root/miniconda3/bin:${PATH}"
+RUN conda install cudatoolkit
+RUN conda install numba
+RUN pip install py-entangle
+RUN conda --version
+RUN which conda
 ENTRYPOINT [ "bash" ]

README.md

@@ -1,4 +1,4 @@
-*This version: 0.1.12*
+*This version: 0.1.13*
 
 ![logo](./images/logo.png)
 
@@ -39,6 +39,13 @@ $ docker build -t entangle .
 $ docker run -it entangle:latest
 root@9579336b3e34:/# python -m entangle.examples.example
 ```
+Or if you have the [NVIDIA Docker Environment](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#docker) setup you can test the numba GPU vector example.
+
+```bash
+$ docker run -it --gpus all entangle
+root@13428af4a37b:/# python -m entangle.examples.example3
+(0.2957176749914652, 0.41134210501331836)
+```
 
 ## Outline
 
@@ -82,7 +89,7 @@ Entangle is a *different* kind of parallel compute framework for multi-CPU/GPU e
 It allows for simple workflow design using *plain old python* and special decorators that control the type of parallel compute and infrastructure needed.
 
 One key feature of entangle is fine-grained control over individual functions in a workflow. You could easily describe multiple functions running across multiple compute environments all interacting as if they were simple local python functions.
-No central scheduler or workflow manager is needed.
+No central scheduler or workflow manager is needed. Choosing where and how functions operate with *declarative infrastructure*.
 
 Another unique quality is the use of composition to build parallel workflows dynamically.
 

entangle/__version__.py

@@ -7,7 +7,7 @@
 
 __title__ = 'py-entangle'
 __description__ = 'A python native parallel processing framework based on simple decorators.'
-__version__ = '0.1.12'
+__version__ = '0.1.13'
 __author__ = 'Darren Govoni'
 __author_email__ = '[email protected]'
 __license__ = 'MIT'