A course of learning LLM inference serving on Apple Silicon for systems engineers: build a tiny vLLM + Qwen.

An Efficient and User-Friendly Scaling Library for Reinforcement Learning with Large Language Models

A high-throughput and memory-efficient inference and serving engine for LLMs

High performance server-side application framework

Retrieval and Retrieval-augmented LLMs

My learning notes for ML SYS.

RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs

Data Agent Ready Warehouse : One for Analytics, Search, AI, Python Sandbox. — rebuilt from scratch. Unified architecture on your S3.

The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.

It's crazy, I found a case where Rust is slower than Python! But, really?

Open Lakehouse Format for Multimodal AI. Convert from Parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, a…

beego is an open-source, high-performance web framework for the Go programming language.

AI-native HTAP database with Git-for-Data and built-in vector search, serving as the data and memory backbone for intelligent agents and applications.

Apache Kvrocks is a distributed key value NoSQL database that uses RocksDB as storage engine and is compatible with Redis protocol.

rust raft with improvements

Apache OpenDAL: One Layer, All Storage.

A persistent key-value storage in rust.

Open-source vector similarity search for Postgres

DatenLord, Computing Defined Storage, an application-orientated, cloud-native distributed storage system

Code examples, data structures, and links from my book, Rust Atomics and Locks.

This is a repo to implement the taomp in go, visible for moers

实现一个操作系统内核

the fastest in-memory index in the East 东半球最快并发索引

A curated PostgreSQL knowledge base covering internals, DBA practices, performance tuning, troubleshooting, ecosystem insights, and real-world production cases.

Introduction for Go's Debug and Profiling from the perspective of engineering

distributed consensus protocol's bugs, flaws, deceptive traps, improvements

This repository contains all the code of algorithms, data-structures and hash function, for which I make videos for my YouTube channel