Day 93

Day 93

Good Lord, so much has happened over the last week and I have so much to write about, but unfortunately can't afford to spend my time on this at the moment... I will update this blog with detailed results of experiments and my thoughts and ideas in regards to the project as soon as I get a chance, promise. Anyway, a short summary of what has happened:

- MPI is faster than serial when learning and optimisation are turned off

- In general, MPI seems to be slower than Serial when optimised mode is on, however, at some very high densities of cortex and retina MPI seems to behave quite differently and seems to outperform Serial. Also, in some cases processing bigger sets of data takes less time than processing smaller sets of data. I find this to be very bizarre, and I really want to find out what's causing this.

- I've built a python script that plots performance graphs and will upload pictures from it soon

- Turning learning on breaks simulations and that's my next thing to fix. Working on it at the moment.

- We also had some ideas in regards to distributing initialisation stage, i.e. generation of Connection Fields, so that all CFs are generated on nodes instead of serially and then distributed. This will give a great performance boost, however this is a bit tricky.

- MPI performance seems to be greatly affected by necessity to communicate the Activity matrix into Serial code on each iteration, and we still have no idea what to do with this.

- At the last skype meeting Jim, my supervisor, has pointed out that successful run of parallel topographica using lissom_oo_or.ty (standard simulation script) and not simplified and trimmed down tiny.ty I'm suing at the moment will signify the end of the project. This seems to be the light in the end of the tunnel. However, at the moment I can't estimate how far I am from it...