Beast code in Giters

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git

Git Source Code Mirror - This is a publish-only repository but pull requests can be turned into patches to the mailing list via GitGitGadget (https://gitgitgadget.github.io/). Please follow Documentation/SubmittingPatches procedure for any of your improvements.

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folly

An open-source C++ library developed and used at Facebook.

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modern-cpp-tutorial

📚 Modern C++ Tutorial: C++11/14/17/20 On the Fly | https://changkun.de/modern-cpp/

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grpc-go

The Go language implementation of gRPC. HTTP/2 based RPC

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vue-manage-system

Vue3、Element Plus、typescript后台管理系统

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muduo

Event-driven network library for multi-threaded Linux server in C++11

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Tinyhttpd

Tinyhttpd 是J. David Blackstone在1999年写的一个不到 500 行的超轻量型 Http Server，用来学习非常不错，可以帮助我们真正理解服务器程序的本质。官网:http://tinyhttpd.sourceforge.net

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grammars-v4

Grammars written for ANTLR v4; expectation that the grammars are free of actions.

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libco

libco is a coroutine library which is widely used in wechat back-end service. It has been running on tens of thousands of machines since 2013.

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Cplusplus-Concurrency-In-Practice

A Detailed Cplusplus Concurrency Tutorial 《C++ 并发编程指南》

Language:C++MIT5262 464 11

shanghai_house_knowledge

2020年11月在上海买房经历总结出来的买房购房做的一些功课分享给大家，技术人帮助技术人，希望对大家有所帮助。

MIT5057 121 13

handy

🔥简洁易用的C++11网络库 / 支持单机千万并发连接 / a simple C++11 network server framework

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phxpaxos

The Paxos library implemented in C++ that has been used in the WeChat production environment.

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PowerVim

Make your vim more power and much easer. 最实用的vim配置🔥

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cmdline

A Command Line Parser

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sql-parser

SQL Parser for C++. Building C++ object structure from SQL statements.

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DeepBSDE

Deep BSDE solver in TensorFlow

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Neural-ODE-Experiments

This repository contains experiments with Neural Ordinary Differential Equations with simulated and real empirical data

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FBSNNs

Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations

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DeepGalerkinMethod

Companion code for "Solving Nonlinear and High-Dimensional Partial Differential Equations via Deep Learning" by A. Al-Aradi, A. Correia, D. Naiff, G. Jardim and Y. Saporito (https://arxiv.org/abs/1811.08782)

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