LingYeAI

LingYeAI's Stars

• DefTruth/Awesome-LLM-Inference

  📖A curated list of Awesome LLM Inference Paper with codes, TensorRT-LLM, vLLM, streaming-llm, AWQ, SmoothQuant, WINT8/4, Continuous Batching, FlashAttention, PagedAttention etc.

  2.7k182

• alibaba/rtp-llm

  RTP-LLM: Alibaba's high-performance LLM inference engine for diverse applications.

  Language:C++52749

• NVIDIA/TensorRT-LLM

  TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT-LLM also contains components to create Python and C++ runtimes that execute those TensorRT engines.

  Language:C++8.4k954

• intel/MTMC-Temporal-Profiler

  Language:Python234

• wsdjeg/Learn-Vim_zh_cn

  聪明地学习Vim

  2.4k301

• LingYeAI/AdderNetCUDA

  An addernet CUDA version.

  Language:Python41

• TouchFishPioneer/SEU-master-thesis

  东南大学硕士研究生学位论文LaTeX模板

  Language:TeX15740

• danielbayevski/PE_for_Eyeriss

  Language:Verilog41

• dldldlfma/eyeriss_v1

  Language:Verilog114

• yzhaiustc/Optimizing-SGEMM-on-NVIDIA-Turing-GPUs

  Optimizing SGEMM kernel functions on NVIDIA GPUs to a close-to-cuBLAS performance.

  Language:Cuda27143

• arasi15/CNN-Accelerator-Implementation-based-on-Eyerissv2

  Language:Verilog8710

• alibaba/heterogeneity-aware-lowering-and-optimization

  heterogeneity-aware-lowering-and-optimization

  Language:C++25276

• pConst/basic_verilog

  Must-have verilog systemverilog modules

  Language:Verilog1.6k376

• taoyilee/clacc

  Deep Learning Accelerator (Convolution Neural Networks)

  Language:Verilog16358

• nvdla/hw

  RTL, Cmodel, and testbench for NVDLA

  Language:Verilog1.7k568

• michaeltinsley/awesome-binary-neural-networks

  A curated list of binary neural network research papers and software packages.

  193

• hpi-xnor/BMXNet-v2-examples

  Examples for BMXNet v2 (https://github.com/hpi-xnor/BMXNet-v2)

  Language:Python92

• huawei-noah/Efficient-AI-Backbones

  Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.

  Language:Python4k706

• Lyken17/pytorch-OpCounter

  Count the MACs / FLOPs of your PyTorch model.

  Language:Python4.9k528

• huawei-noah/AdderNet

  Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"

  Language:Python953187

• NVlabs/timeloop

  Timeloop performs modeling, mapping and code-generation for tensor algebra workloads on various accelerator architectures.

  Language:C++335101

• MingSun-Tse/Efficient-Deep-Learning

  Collection of recent methods on (deep) neural network compression and acceleration.

  925133

• Accelergy-Project/accelergy

  Accelergy is an energy estimation infrastructure for accelerator energy estimations

  Language:Python12440

• iamhankai/ghostnet.pytorch

  [CVPR2020] GhostNet: More Features from Cheap Operations

  Language:Python522116

• ultralytics/yolov3

  YOLOv3 in PyTorch > ONNX > CoreML > TFLite

  Language:Python10.2k3.4k

• pprp/voc2007_for_yolo_torch

  :punch: Prepare VOC format datasets for ultralytics/yolov3 & yolov5

  Language:Python19657

• HewlettPackard/cacti

  An integrated cache and memory access time, cycle time, area, leakage, and dynamic power model

  Language:C++396136

• fengbintu/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.

  1.9k381

• basicmi/AI-Chip

  A list of ICs and IPs for AI, Machine Learning and Deep Learning.

  Language:PHP1.6k274

• vineodd/PIMSim

  PIMSim is a Process-In-Memory Simulator with the compatibility of GEM5 full-system simulation.

  Language:C++18286