CIMFlow

GitHub: https://github.com/BUAA-CI-LAB/CIMFlow

Website: https://www.cimflow.org

CIMFlow is an open-source framework for Computation-in-Memory (CIM) accelerator design and simulation. It provides a comprehensive toolchain for building, profiling, and optimizing CIM architectures, enabling researchers to rapidly prototype and evaluate novel memory-centric computing systems.

Literature on Graph Neural Networks Acceleration

GitHub: https://github.com/BUAA-CI-LAB/Literatures-on-GNN-Acceleration

This repository collects key literature on graph neural network acceleration, covering algorithmic optimizations, hardware-aware architectures, and efficient inference methods. It is a useful starting point for researchers exploring GNN performance on edge and accelerator platforms.

Literature on SRAM-based Compute-In-Memory

GitHub: https://github.com/BUAA-CI-LAB/Literatures-on-SRAM-based-CIM

This repository collects references on SRAM-based compute-in-memory systems, including circuit-level designs, architectural techniques, and system-level evaluation. It helps researchers find foundational work and recent advances in SRAM CIM acceleration.