Blog Post 3
Muiredach O’Riain
week: 3
Starting: 15th July 2019 – 15/7/19
GNN –
Embedded Tools & User Permissions
An exciting development for this project came early in the week when I was put in touch with Roger Dev, the leader of HPCC Systems Machine Learning Library. Roger and his team are currently developping a Generalized Neural Network (GNN) Bundle for use with HPCC systems, which will eventually be a distributed ECL interface to Tensorflow
Over the coming weeks I plan to utilise an Alpha version of this tool set in order to help construct and develop Neural Nets with my data using ECL rather than with embedded python code as was originally my plan. This could be a huge boost for this project in terms of productivity as it would allow me more flexibility when coding with ECL rather than swapping back and forth between ECL and Python. Using the Alpha also offers a unique opportunity to be one of the first people outside of the Dev team to test the GNN bundle and help contribute to its development.
Permissions & Setbacks-
This week has been a bit slower in terms of actaul development compared to the previous two. Due to an issue with admin rights on my work machine I have been unable to download the necessary software to begin working with ECL and HPCC systems.
Despite this setback I am still ahead of schedule having previously surpassed my predicted goals from my proposal. Furthermore the downtime I have had whilst working to resolve this issue has allowed me to brush up on the ECL language and surrounding documentation, which I feel will help greatly improve my programming in the coming weeks.
This week constitued a break from programming and allowed me some time to reflect on the direction of the project and my approaches to the problems it presents.
Next week my goals are :
Get ECL-IDE & HPCC Systems Running on work machine
Figure out the best data format to use and spray my data to a cluster
Get to grips with ECL and begin some tests with ECL on my data
Begin to look at the GNN Alpha starting with the provided Documentation