无聊的小黑's repositories
eyeriss-chisel3
eyeriss-chisel3
brevitas
Brevitas: quantization-aware training in PyTorch
CompressionData
The training data of learned image compression. The data is from flicker.com.
cora-docs
Developer documentation for the Cora project.
CycleGAN
Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
equation-contracts
This repository contains the smart contracts for Equation. Please visit https://equation.org to learn more.
finn-hlslib
Vivado HLS library for FINN
Game-Programmer-Study-Notes
:anchor: 我的游戏程序员生涯的读书笔记合辑。你可以把它看作一个加强版的Blog。涉及图形学、实时渲染、编程实践、GPU编程、设计模式、软件工程等内容。Keep Reading , Keep Writing , Keep Coding.
mempool
A 256-RISC-V-core system with low-latency access into shared L1 memory.
musegan
An AI for Music Generation
ncnn
ncnn is a high-performance neural network inference framework optimized for the mobile platform
onnx
Open standard for machine learning interoperability
oscpu-framework
A Verilator-based demo.
pypianoroll
A toolkit for working with piano rolls
rgb000000.github.io
rgb000000 blog
riscv-sodor
educational microarchitectures for risc-v isa
soDLA
A Self-driving car Optimized DLA
tensorflow
An Open Source Machine Learning Framework for Everyone
TNN
TNN: developed by Tencent Youtu Lab and Guangying Lab, a lightweight and high-performance deep learning framework for mobile inference. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework. TNN：由腾讯优图实验室和光影实验室协同打造，移动端高性能、轻量级推理框架，同时拥有跨平台、高性能、模型压缩、代码裁剪等众多突出优势。TNN框架在原有Rapidnet、ncnn框架的基础上进一步加强了移动端设备的支持以及性能优化，同时也借鉴了业界主流开源框架高性能和良好拓展性的优点。目前TNN已经在手Q、微视、P图等应用中落地，欢迎大家参与协同共建，促进TNN推理框架进一步完善。
ultra_net
FPGA-based neural network inference project for 2020 DAC System Design Contest
XiangShan
Open-source high-performance RISC-V processor