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. 2011 May 4;6(5):e18539. doi: 10.1371/journal.pone.0018539

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Richmond et al.

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.

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Figure shows the performance profile of our GPU implementation with respect to where GPU time is spent during the simulation (shown as a percentage for each GPU kernel corresponding with figure 8). The figure in brackets next to the vertical axis label indicates the total number of times the kernel function is called over single “learn step” with a total time simulation period of T = 128 and . An additional amount of CPU time is also required however this is negligible in the scale of the overall simulation. A: Represents the case for our model without lateral connections. B: Represents a case with lateral connections which is the same however it includes a kernel function “actionCellLateralSpikePropagation” which performs the lateral spike propagation simulation.

Inline graphic — Figure shows the performance profile of our GPU implementation with respect to where GPU time is spent during the simulation (shown as a percentage for each GPU kernel corresponding with figure 8). The figure in brackets next to the vertical axis label indicates the total number of times the kernel function is called over single “learn step” with a total time simulation period of T = 128 and . An additional amount of CPU time is also required however this is negligible in the scale of the overall simulation. A: Represents the case for our model without lateral connections. B: Represents a case with lateral connections which is the same however it includes a kernel function “actionCellLateralSpikePropagation” which performs the lateral spike propagation simulation.