alphaRGB

activitywatch

The best free and open-source automated time tracker. Cross-platform, extensible, privacy-focused.

FP8-Emulation-Toolkit

PyTorch extension for emulating FP8 data formats on standard FP32 Xeon/GPU hardware.

ppq

PPL Quantization Tool (PPQ) is a powerful offline neural network quantization tool.

smoothquant

[ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

llmtools

Finetuning Large Language Models on One Consumer GPU in Under 4 Bits

Quantformer

This is the official pytorch implementation for the paper: *Quantformer: Learning Extremely Low-precision Vision Transformers*.

micronet

micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape

Paper-Writing-Tips

Paper Writing Tips

Neural-Networks-on-Silicon

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.

GEMM_WMMA

GEMM by WMMA (tensor core)

ConvNN

A simple CNN training framework support on CPU and GPU(CUDNN)

Deep-Learning-Accelerator-SW

NVIDIA DLA-SW, the recipes and tools for running deep learning workloads on NVIDIA DLA cores for inference applications.

cuda-tensorcore-hgemm

NiuDianNao

A simple cycle-accurate DaDianNao simulator

HolisticTraceAnalysis

A library to analyze PyTorch traces.

nvitop

An interactive NVIDIA-GPU process viewer and beyond, the one-stop solution for GPU process management.

TPU-Tensor-Processing-Unit

IC implementation of TPU

gpgpu-sim_distribution

GPGPU-Sim provides a detailed simulation model of contemporary NVIDIA GPUs running CUDA and/or OpenCL workloads. It includes support for features such as TensorCores and CUDA Dynamic Parallelism as well as a performance visualization tool, AerialVisoin, and an integrated energy model, GPUWattch.

Computer-Science-Textbooks

Collect some CS textbooks for learning.

Integrated-Circuit-Textbooks

Collect some IC textbooks for learning.

viztracer

VizTracer is a low-overhead logging/debugging/profiling tool that can trace and visualize your python code execution.

cudnnConvolutionTest

cuda-sgemm

goldeneye

GoldenEye is a functional simulator with fault injection capabilities for common and emerging numerical formats, implemented for the PyTorch deep learning framework.

PWLQ

Code for our paper at ECCV 2020: Post-Training Piecewise Linear Quantization for Deep Neural Networks

awesome-model-quantization

A list of papers, docs, codes about model quantization. This repo is aimed to provide the info for model quantization research, we are continuously improving the project. Welcome to PR the works (papers, repositories) that are missed by the repo.

AdaptivFloat

Adaptive floating-point based numerical format for resilient deep learning

Deep-Compression-AlexNet

Deep Compression on AlexNet

RobustViT

[NeurIPS 2022] Official PyTorch implementation of Optimizing Relevance Maps of Vision Transformers Improves Robustness. This code allows to finetune the explainability maps of Vision Transformers to enhance robustness.

DynamicViT

[NeurIPS 2021] [T-PAMI] DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification