I've got a technique where I simply record every spike event, its tick, source & target in a SQL database. This allows for quick recursive queries for determini

I've got a technique where I simply record every spike event, its tick, source & target in a SQL database. This allows for quick recursive queries for determining contributors to output. I feel if we stop chasing biological emulation and superscalar, we can start to get clever with more traditional data-wrangling methods. I don't think the answer to a high quality SNN model is going to require purpose-built hardware or a supercomputer to run. I think you will see emergence even with extremely rudimentary single core CPU-bound models if everything else is done well. Event-driven is a superpower when architected correctly in software. This means you can pick clever algorithms and lazily-evaluate the network. Implications being that networks that would ordinarily be impossible to simulate in real time can now be simulated this way. You could have neuron state in offline storage that is brought online as relevant action potentials are enqueued for future execution.