# Faster and Simpler SNN Simulation with Work Queues

arXiv: https://arxiv.org/abs/1912.07423 · HTML: https://mlsanity.com/paper/1912.07423/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Dec 2019.

## Built on by (most cited first, 2 of 2)

- [Multi-GPU SNN Simulation with Static Load Balancing](https://mlsanity.com/paper/2102.04681/) (2021)
- [Even Faster SNN Simulation with Lazy+Event-driven Plasticity and Shared Atomics](https://mlsanity.com/paper/2107.04092/) (2021)

## Abstract (arXiv)

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.