hcysky's starred repositories
SecureLoop-MICRO2023Artifact
MICRO2023 Artifact Evaluation of SecureLoop
scale-sim-v2
Repository to host and maintain scale-sim-v2 code
deep-learning-models
Keras code and weights files for popular deep learning models.
ramulator2
Ramulator 2.0 is a modern, modular, extensible, and fast cycle-accurate DRAM simulator. It provides support for agile implementation and evaluation of new memory system designs (e.g., new DRAM standards, emerging RowHammer mitigation techniques). Described in our paper https://people.inf.ethz.ch/omutlu/pub/Ramulator2_arxiv23.pdf
deeplearning_ai_books
deeplearning.ai(吴恩达老师的深度学习课程笔记及资源)
cs231n.github.io
Public facing notes page
Latex-Templates
A concise set of Latex templates that serves a small set of needs - CV, Essays, Articles and Problem Sets
CNN-using-HLS
Convolutional Neural Network Using High Level Synthesis
dnnweaver2
Open Source Specialized Computing Stack for Accelerating Deep Neural Networks.
Reactive-Resume
A one-of-a-kind resume builder that keeps your privacy in mind. Completely secure, customizable, portable, open-source and free forever. Try it out today!
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
efficientvit
EfficientViT is a new family of vision models for efficient high-resolution vision.
finn-hlslib
Vitis HLS Library for FINN
Vitis-Tutorials
Vitis In-Depth Tutorials
Vitis_Libraries
Vitis Libraries
OpenCL-Guide
A guide to help developers get up and running quickly with the OpenCL programming framework
conv_arithmetic
A technical report on convolution arithmetic in the context of deep learning