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.

翻译：存内计算（PIM）在加速神经网络方面展现出非凡潜力。为评估PIM加速器的性能，本文提出一种基于ISA的仿真框架，包含针对在PIM架构上运行的神经网络的专用ISA、编译器以及周期精确可配置仿真器。与现有工作相比，本工作通过所提出的ISA实现软件算法与硬件架构的解耦，为评估软硬件优化的有效性提供了更便捷的途径。该仿真器采用事件驱动模拟方法，对硬件并行性具有更好的支持。本框架已在https://github.com/wangxy-2000/pimsim-nn开源。