Skip to content Dr Martin Peniak Robotics · Cameras · Coordinates · Place

Legacy article – Robotics, GPU and research

Multi-GPU back-propagation through time

Original publication date
27 July 2012
Original section
Robotics, GPU and research
Original slug / legacy ID
multi-gpu-back-propagation-through-time / 283
Restored on current site
martinpeniak.com/archive/writing/multi-gpu-back-propagation-through-time/
Editing scope
Period voice retained; spelling and formatting lightly cleaned.

Originally published 27 July 2012 on the earlier martinpeniak.com site.

Preserved from the old research notes as a full article. The article keeps its period voice, with light formatting cleanup.

We have implemented a multi-GPU version of the back-propagation through time algorithm for the training of MTRNN (multiple time-scales recurrent neural network). We have also tested the code on 4xGPU setups and the preliminary result show excellent scaling. From the graph you can see that when we use 2 GPUs we get almost perfect 2x speedup over single GPU; when we use 3 GPUs we get nearly 3x speed, etc.


We are now starting to develop scalable genetic algorithms for large genotypes making good use of GPU-based fitness evaluations. 


All these developments will be added to Aquila 2.0. New developers are welcome, contact me if you are interested.

CPU vs GPU