Comments (5)
In the synapses
kernel we have a thread <-> synapse
correspondence, where in heterogeneous delay mode the synapses are sorted by delays and in homogeneous delay mode by synapse IDs. Therefore the writes to postsynaptic neurons will very likely not be coalesced (depending on the synapse creation, e.g. for all to all connections synapse IDs might already be sorted by postsynaptic neuron IDs). Sorting the synapses by postsynaptic neuron IDs (in heterogeneous delay mode only within the same delay) could increase coalescing.
EDIT: probably only useful to coalescing if a pre neuron is connected to e.g. all post neurons. So user preferences make sense here.
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heterog mode:
- bundle queues: simply sort bundles in target mode by target neurons, in synapse mode by synapse ids
- synapse queues: we would have to sort the spikequeues in each timestep and we will put this to wishlist (if useful at all)
homog mode
- sort connectivity matrix w.r.t. post neuron in target mode and w.r.t. synapse id in synapse mode
ensure that performance with standard examples does not degrade
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Also check again what I wrote in #30
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Special case to take into account:
If there is only one synaptic pathway direction (either pre->post or post->pre, not both), then all synapses should just be relabeled once they are sorted into the connectivity matrix, such that the synapse IDs are consecutive in the connectivity matrix. This makes the connectivity matrix obsolete an lets all synapse variable automatically be stored in the connectivity matrix structure, allowing coalesced memory accesses. If there are both synaptic pathway directions, variables can only be sorted for one of them (Brette2012 review). In that case, the graph-cut idea might be interesting.
This all should in the best case already be happening during synapse creation (if possible), by changing the looping order (e.g. first over pre then over post neurons to sort by post per synapses group, as is likely happening by default). Should be tackled together with #177 .
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Any sorting of synaptic variables would require some mechanism for sorting variables (and potentially monitor recordings) back into the format expected on Python side, see my comment in #271.
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Related Issues (20)
- Call reset kernel only with as many threads as there are spiking neurons (not as there are neurons in total)
- Refactor benchmarking scripts and update generated plots
- Check if storing the size of synapse groups is necessary? HOT 1
- Needs patch to run with Brian 2.4.2 HOT 2
- Optimize `StateMonitor`
- Impelement brian2cuda preference file support
- Copy all eventspace counters to host efficiently at each time step
- Investigate and document performance effects when working with `Subgroup`s HOT 1
- Consider partitioning eventspaces when using `Subgroup`s HOT 4
- Optimize `PopulationRateMonitor`
- Fix `SpikeMonitor` for `Subgroup`s HOT 1
- Optimize our `SpikeMonitor` for `Subgroups`
- Refactor test suite scripts
- Fix `ReferencError` in spatialneuron tests HOT 3
- Fix memory leak when having multiple `run` calls
- Spikes are lost when changing delays between `run` calls HOT 3
- Recent Brian2 update PR broke benchmark scripts HOT 1
- Brian2Cuda Uninstalls Brian2 2.5.1 and Installs 2.4.2 Which Won't Import HOT 3
- Brian2Hears and Brian2CUDA HOT 3
- Optimise brian2CUDA HOT 2
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