First Open-Source Industry-Specific Model for Semiconductors

The Yu (羽) programming language.

Accelergy is an energy estimation infrastructure for accelerator energy estimations

AIFoundation 主要是指AI系统遇到大模型，从底层到上层如何系统级地支持大模型训练和推理，全栈的核心技术。

RISC-V-based many-core neuromorphic architecture

Writing AI Conference Papers: A Handbook for Beginners

HW Architecture-Mapping Design Space Exploration Framework for Deep Learning Accelerators

Multi-core HW accelerator mapping optimization framework for layer-fused ML workloads.

STONNE: A Simulation Tool for Neural Networks Engines

Code for paper: Spiking Token Mixer: An Event-Driven Friendly Former Structure for Spiking Neural Networks

[NeurIPS 2024] Advancing Training Efficiency of Deep Spiking Neural Networks through Rate-based Backpropagation

Simulation of Advanced Neuromorphic Architectures for Fast Exploration

Offical implementation of "Integer-Valued Training and Spike-Driven Inference Spiking Neural Network for High-performance and Energy-efficient Object Detection" (ECCV2024 Best Paper Candidate)

PicoRV32 - A Size-Optimized RISC-V CPU

[CVPR Workshop 2024] Retina is an eye tracking method suitable for deployment on a neuromorphic system on chip.

End-to-End Autonomous Driving with Spiking Neural Networks

YOLOv10: Real-Time End-to-End Object Detection [NeurIPS 2024]

A nifty visual presentation of a Spiking Neural Network (SNN)

Offical Implementation of "CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks" (ICML 2024 spotlight)

The original sources of MS-DOS 1.25, 2.0, and 4.0 for reference purposes

Brain-inspired multimodal hybrid neural network for robot place recognition

A minimal GPU design in Verilog to learn how GPUs work from the ground up

Spiking Global-Local Fusion Transformer

Offical code of "QKFormer: Hierarchical Spiking Transformer using Q-K Attention" (NeurIPS 2024，Spotlight 3%)

MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.

About Code release for "Flowformer: Linearizing Transformers with Conservation Flows" (ICML 2022), https://arxiv.org/pdf/2202.06258.pdf