  We present a clock-driven Spiking Neural Network simulator which is up to 3x
faster than the state of the art while, at the same time, being more general
and requiring less programming effort on both the user's and maintainer's side.
This is made possible by designing our pipeline around "work queues" which act
as interfaces between stages and greatly reduce implementation complexity. We
evaluate our work using three well-established SNN models on a series of
benchmarks.
