  Processing-in-memory (PIM) has shown extraordinary potential in accelerating
neural networks. To evaluate the performance of PIM accelerators, we present an
ISA-based simulation framework including a dedicated ISA targeting neural
networks running on PIM architectures, a compiler, and a cycleaccurate
configurable simulator. Compared with prior works, this work decouples software
algorithms and hardware architectures through the proposed ISA, providing a
more convenient way to evaluate the effectiveness of software/hardware
optimizations. The simulator adopts an event-driven simulation approach and has
better support for hardware parallelism. The framework is open-sourced at
https://github.com/wangxy-2000/pimsim-nn.
