fantasysee

academicpages.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

awesome-quantization-and-fixed-point-training

Neural Network Quantization & Low-Bit Fixed Point Training For Hardware-Friendly Algorithm Design

Basys3

berkeley-stat-157

Homepage for STAT 157 at UC Berkeley

flops-counter.pytorch

Flops counter for convolutional networks in pytorch framework

Git4Beginners_ICAIS

A brief tutorial of Git for beginners

h265-encoder-rtl

pku-cs-self-learning

计算机自学指南

PDPU

PDPU: An Open-Source Posit Dot-Product Unit for Deep Learning Applications

BEBERT

BEBERT: Efficient and Robust Binary Ensemble BERT

fantasysee/pku-cs-self-learning

计算机自学指南

fantasysee/academicpages.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

fantasysee/awesome-quantization-and-fixed-point-training

Neural Network Quantization & Low-Bit Fixed Point Training For Hardware-Friendly Algorithm Design

fantasysee/Basys3

fantasysee/berkeley-stat-157

Homepage for STAT 157 at UC Berkeley

fantasysee/flops-counter.pytorch

Flops counter for convolutional networks in pytorch framework

fantasysee/Git4Beginners_ICAIS

A brief tutorial of Git for beginners

fantasysee/h265-encoder-rtl

fantasysee/numpy-posit

posit (unum type III) integrated Numpy

fantasysee/Open-Source-IPs

fantasysee/Open-Source-Network-on-Chip-Router-RTL

fantasysee/pytorch-OpCounter

Count the MACs / FLOPs of your PyTorch model.

fantasysee/pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

fantasysee/SciencePlots

Matplotlib styles for scientific plotting

fantasysee/verible

Verible is a suite of SystemVerilog developer tools, including a parser, style-linter, and formatter.

fantasysee/wincnn

Winograd minimal convolution algorithm generator for convolutional neural networks.