Stars
A list of ICs and IPs for AI, Machine Learning and Deep Learning.
[ASPLOS 2024] CIM-MLC: A Multi-level Compilation Stack for Computing-In-Memory Accelerators
Analyze the inference of Large Language Models (LLMs). Analyze aspects like computation, storage, transmission, and hardware roofline model in a user-friendly interface.
thu-nics / UniNDP
Forked from godfather991/UniNDPGithub repository of HPCA 2025 paper "UniNDP: A Unified Compilation and Simulation Tool for Near DRAM Processing Architectures"
Artifact material for [HPCA 2025] #2108 "UniNDP: A Unified Compilation and Simulation Tool for Near DRAM Processing Architectures"
CIM-MLC is a multi-level compilation stack for computing-in-memory accelerators
Awesome LLM compression research papers and tools.
MambaOut: Do We Really Need Mamba for Vision? (CVPR 2025)
Reading list for research topics in multimodal machine learning
Tool for optimize CNN blocking
This is originally a collection of papers on neural network accelerators. Now it's more like my selection of research on deep learning and computer architecture.
Automatic generation of FPGA-based learning accelerators for the neural network family
Automatically exported from code.google.com/p/cuda-convnet2
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)
Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1
Some example dockerfiles for use with Docker