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100-gcc-tips

A collection of gcc tips. 100 maybe just mean many here.

100-gdb-tips

A collection of gdb tips. 100 maybe just mean many here.

as

awesome-machine-learning-in-compilers

Must read research papers and links to tools and datasets that are related to using machine learning for compilers and systems optimisation

c910-llvm

平头哥玄铁C910的LLVM工具链支持，由PLCT实验室提供，非官方版本

coremarkpro-util-make-riscv

The utility files to port CoreMark-Pro to RISC-V.

count_reg_spill

This program can count register spill in the assembly code

hellogcc.github.io

Rebuild the hellogcc.org using markdown and github.io

l919898756.github.io

llama.cpp

Port of Facebook's LLaMA model in C/C++

llvm-tutorial-cn

Simplified Chinese translation for the LLVM Tutorial

llvm_for_cpu0

This is a tutorial to learn LLVM, I realize a backend to compiler machine code for cpu0 which is a simple RISC cpu.

mockingbird

🚀AI拟声: 5秒内克隆您的声音并生成任意语音内容 Clone a voice in 5 seconds to generate arbitrary speech in real-time

ocolos-public

Ocolos is the first online code layout optimization system for unmodified applications written in unmanaged languages.

openarkcompiler

方舟编译器源代码（手动镜像）

openbilibili

perf-ninja

This is an online course where you can learn and master the skill of low-level performance analysis and tuning.

psychic-pancake

risc-v

This is a compiled riscv tools chain

risc-v_article_paper_src

riscv资料、论文等

riscv

This is a compiled riscv tool chain

safec

safec'log count

tnn

TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. 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.

tvmdoc