https://github.com/coderonion/awesome-max-mojo

A collection of some awesome public MAX platform, Mojo programming language projects.
https://github.com/coderonion/awesome-max-mojo

awesome basalt chris-lattner cpp cuda large-language-models llama llama3 llm llvm machine-learning mlir modular mojo numpy pytorch rust tensor yolo yolov10

Last synced: 3 months ago
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A collection of some awesome public MAX platform, Mojo programming language projects.

• Host: GitHub
• URL: https://github.com/coderonion/awesome-max-mojo
• Owner: coderonion
• Created: 2024-02-29T15:16:24.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2024-08-18T12:16:06.000Z (4 months ago)
• Last Synced: 2024-10-05T13:02:19.835Z (3 months ago)
• Topics: awesome, basalt, chris-lattner, cpp, cuda, large-language-models, llama, llama3, llm, llvm, machine-learning, mlir, modular, mojo, numpy, pytorch, rust, tensor, yolo, yolov10
• Homepage:
• Size: 19.5 KB
• Stars: 16
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• ultimate-awesome - awesome-max-mojo - A collection of some awesome public MAX platform, Mojo programming language projects. (Programming Language Lists / Mojo Lists)

README

        
# Awesome-MAX-Mojo-MLIR

[![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)

This repository lists some awesome public MAX platform, Mojo programming language and Multi-Level IR Compiler Framework(MLIR) projects.

## Contents

- [Awesome-MAX-Mojo-MLIR](#awesome-MAX-Mojo-mlir)

  - [Summary](#summary)

    - [Official Version](#official-version)

    - [Awesome List](#awesome-list)

    - [Learning Resources](#learning-resources)

      - [MAX Learning](#max-learning)

      - [Mojo Learning](#mojo-learning)

      - [MLIR Learning](#mlir-learning)

  - [Model Compilation](#model-compilation)

  - [Performance Benchmark](#performance-benchmark)

  - [Package and Version Manager](#package-and-version-manager)

  - [Data Structure and Algorithm](#data-structure-and-algorithm)

  - [FFI Bindings](#ffi-bindings)

  - [GPU Programming](#gpu-programming)

  - [Scientific Computation](#scientific-computation)

    - [Numerical Calculation](#numerical-calculation)

    - [Linear Algebra](#linear-algebra)

  - [Machine Learning](#machine-learning)

    - [Machine Learning Framework](#machine-learning-framework)

    - [Large Language Model](#large-language-model)

    - [AI Generated Content](#ai-generated-content)

    - [Image Recognition](#image-recognition)

    - [Object Detection](#object-detection)

  - [Test Framework](#test-framework)

  - [Command Line Interpreter](#command-line-interpreter)

  - [Parser](#parser)

  - [Database](#database)

  - [Date and Time](#date-and-time)

  - [Embedded Development](#embedded-development)

  - [File Processing](#file-processing)

  - [Image Processing](#image-processing)

  - [Hash Function](#hash-function)

  - [HTTP Framework](#http-framework)

  - [TCP Framework](#tcp-framework)

  - [Web Framework](#web-framework)

  - [Translation](#translation)

  - [Quantitative Trading](#quantitative-trading)

  - [Data Storing and Processing](#data-storing-and-processing)

  - [GUI](#gui)

  - [Blogs](#blogs)

  - [Videos](#videos)

  - [Jobs and Interview](#jobs-and-interview)

## Summary

  - ### Official Version

    - [Mojo🔥](https://github.com/modularml/mojo)  : The Mojo Programming Language. Mojo is a new programming language that bridges the gap between research and production by combining Python syntax and ecosystem with systems programming and metaprogramming features. Mojo is still young, but it is designed to become a superset of Python over time. [docs.modular.com/mojo](https://docs.modular.com/mojo).

    - [Mojo std](https://docs.modular.com/mojo/lib) : These are all the modules in the Mojo standard library.

    - [Mojo Playground](https://docs.modular.com/mojo/playground) : The Mojo Playground.

    - [MAX](https://www.modular.com/max) : MAX is an integrated, composable suite of products that simplifies your AI infrastructure so you can develop, deploy, and innovate faster.

    - [MLIR](https://mlir.llvm.org/) : Multi-Level Intermediate Representation.

    - [LLVM](https://llvm.org/) : The LLVM Compiler Infrastructure.

    - [llvm/llvm-project](https://github.com/llvm/llvm-project)  : The LLVM Project is a collection of modular and reusable compiler and toolchain technologies. [llvm.org](http://llvm.org/)

  - ### Awesome List

    - [mojo-cc/awesome-max-mojo-mlir](https://github.com/mojo-cc/awesome-max-mojo-mlir)  : A collection of some awesome public MAX platform, Mojo programming language and Multi-Level IR Compiler Framework(MLIR) projects.

    - [ego/awesome-mojo](https://github.com/ego/awesome-mojo)  : Awesome Mojo🔥 [awesome.mojo-lang.dev](https://awesome.mojo-lang.dev/)

    - [mojicians/awesome-mojo](https://github.com/mojicians/awesome-mojo)  : A curated list of awesome Mojo 🔥 frameworks, libraries, software and resources.

    - [mfranzon/mojo-is-awesome](https://github.com/mfranzon/mojo-is-awesome)  : Curated list of Mojo resources, benchmarks and examples 🔥

    - [feep/awesome-mojo](https://github.com/feep/awesome-mojo)  : Mojo lang🔥: so awesome it wears sunglasses to protect you.

    - [mojo-cn/awesome-mojo-cn](https://github.com/mojo-cn/awesome-mojo-cn)  : Mojo 生态资源推荐。

  - ### Learning Resources

    - #### MAX Learning

        - [MAX Docs](https://docs.modular.com/max/) : The Modular Accelerated Xecution (MAX) platform is a unified set of APIs and tools that help you build and deploy high-performance AI pipelines.

    - #### Mojo Learning

        - [Mojo Docs](https://docs.modular.com/mojo/manual/) : Welcome to the Mojo Manual, a complete guide to the Mojo🔥 programming language!

        - [Mojo Dojo](https://mojodojo.dev/) : Learning Resources for Mojo 🔥

        - [rd4com/mojo-learning](https://github.com/rd4com/mojo-learning)  : 📖 Learn some mojo !

        - [helehex/mojo-test](https://github.com/helehex/mojo-test)  : mojo examples, tests, and ideas.

        - [Brian-M-J/sicp_mojo](https://github.com/Brian-M-J/sicp_mojo)  : A port of Structure and Interpretation of Computer Programs to Mojo🔥

        - [bumbii/code](https://github.com/bumbii/code)  : Coding exercises in multiple programming languages (Python, Mojo...). [bumbii.tech](https://bumbii.tech/)

        - [HaruTzuki/MojoLessons](https://github.com/HaruTzuki/MojoLessons)  : MojoLessons.

    - #### MLIR Learning

        - [LLVM Docs](https://llvm.org/docs/) : LLVM Documentation.

        - [MLIR Docs](https://mlir.llvm.org/docs/) : MLIR Code Documentation.

        - [BBuf/tvm_mlir_learn](https://github.com/BBuf/tvm_mlir_learn)  : compiler learning resources collect.

        - [j2kun/mlir-tutorial](https://github.com/j2kun/mlir-tutorial)  : This is the code repository for a series of articles on the [MLIR framework](https://mlir.llvm.org/) for building compilers.

        - [KEKE046/mlir-tutorial](https://github.com/KEKE046/mlir-tutorial)  : Hands-On Practical MLIR Tutorial.

## Model Compilation

  - [ByteIR](https://github.com/bytedance/byteir)  : The ByteIR Project is a ByteDance model compilation solution. ByteIR includes compiler, runtime, and frontends, and provides an end-to-end model compilation solution. [byteir.ai](https://byteir.ai/)

## Performance Benchmark

  - [Benny-Nottonson/Mojo-Marathons](https://github.com/Benny-Nottonson/Mojo-Marathons)  : Mojo Marathons 🔥. Welcome to Mojo Marathons, a monthly competition where the best Mojicians showcase their skills and push Mojo to its limits. Compete for prizes and recognition! 🏆

  - [MoSafi2/BlazeSeq](https://github.com/MoSafi2/BlazeSeq)  : BlazeSeq🔥. Community Spotlight: Outperforming Rust ⚙️ DNA sequence parsing benchmarks by 50% with Mojo 🔥.

  - [manatlan/sudoku_resolver](https://github.com/manatlan/sudoku_resolver)  : just to compare perf between mojo, nim, java, nodejs, rust and python3 of a same algo.

  - [jiel/laplacian_filters_benchmark](https://github.com/jiel/laplacian_filters_benchmark)  : benchmark of python and mojo implementations of the Laplacian filter (edge detection).

  - [dev0x13/gemm-benchmark-2023](https://github.com/dev0x13/gemm-benchmark-2023)  : Benchmarks for modern (2023) high-performance floating-point GEMM implementations.

  - [RedKinda/mojo-benchmarks](https://github.com/RedKinda/mojo-benchmarks)  : mojo-benchmarks.

  - [RicRax/mojo_vs_python](https://github.com/RicRax/mojo_vs_python)  : Different benchmarks implemented in mojo and python.

  - [vincentme/onnx-kmeans](https://github.com/vincentme/onnx-kmeans)  : 使用ONNX实现传统算法——以Kmeans聚类为例并和python/mojo实现对比; Using ONNX to implement traditional algorithms - taking Kmeans clustering as an example and comparing it with python/mojo.

## Package and Version Manager

  - [Hammad-hab/pkm](https://github.com/Hammad-hab/pkm)  : Mojo's unoffical package manager.

## Data Structure and Algorithm

  - [mzaks/compact-dict](https://github.com/mzaks/compact-dict)  : A fast and compact Dict implementation in Mojo 🔥

  - [mikowals/dynamic_vector.mojo](https://github.com/mikowals/dynamic_vector.mojo)  : An experimental drop-in replacement for Mojo stdlib DynamicVector that demonstrates new features using References.

  - [Honkware/sort.mojo](https://github.com/Honkware/sort.mojo)  : sorting algorithms written in Mojo.

  - [mzaks/mojo-flx](https://github.com/mzaks/mojo-flx)  : FlexBuffers implementation in Mojo.

  - [mzaks/mojo-trees](https://github.com/mzaks/mojo-trees)  : Experimental Tree data structures in Mojo.

  - [mzaks/mojo-sort](https://github.com/mzaks/mojo-sort)  : Implementation of different sorting algorithms in Mojo.

## FFI Bindings

  - [spcl/pymlir](https://github.com/spcl/pymlir)  : Python interface for MLIR - the Multi-Level Intermediate Representation.

  - [ihnorton/mojo-ffi](https://github.com/ihnorton/mojo-ffi)  : Mojo FFI Notes.

  - [Benny-Nottonson/glibc.mojo](https://github.com/Benny-Nottonson/glibc.mojo)  : A wrapper around GLibC for use in Mojo programs, provides higher level functions for accessing C system calls.

## GPU Programming

  - ['gpu' Dialect](https://mlir.llvm.org/docs/Dialects/GPU/) : This dialect provides middle-level abstractions for launching GPU kernels following a programming model similar to that of CUDA or OpenCL.

  - ['amdgpu' Dialect](https://mlir.llvm.org/docs/Dialects/AMDGPU/) : The AMDGPU dialect provides wrappers around AMD-specific functionality and LLVM intrinsics.

  - [AyakaGEMM/Hands-on-MLIR](https://github.com/AyakaGEMM/Hands-on-MLIR)  : Hands-on-MLIR.

  - [yao-jiashu/KernelCodeGen](https://github.com/yao-jiashu/KernelCodeGen)  : GEMM/Conv2d CUDA/HIP kernel code generation using MLIR.

## Scientific Computation

  - ### Numerical Calculation

    - [helehex/moplex](https://github.com/helehex/moplex)  : Generalized complex numbers for Mojo🔥

    - [helehex/monums](https://github.com/helehex/monums)  : Strange numbers for Mojo🔥

    - [helehex/infrared](https://github.com/helehex/infrared)  : Geometric Algebra for Mojo🔥

    - [keittlab/numojo](https://github.com/keittlab/numojo)  : Numerics for Mojo.

  - ### Linear Algebra

    - [YichengDWu/matmul.mojo](https://github.com/YichengDWu/matmul.mojo)  : High Performance Matrix Multiplication in Pure Mojo 🔥. Matmul.🔥 is a high performance muilti-threaded implimentation of the [BLIS](https://en.wikipedia.org/wiki/BLIS_(software)) algorithm in pure Mojo 🔥.

    - [codingonion/moblas](https://github.com/codingonion/moblas)  : BLAS (Basic Linear Algebra Subprograms) library written in mojo programming language.

    - [Mojo-Numerics-and-Algorithms-group/NuMojo](https://github.com/Mojo-Numerics-and-Algorithms-group/NuMojo)  : A numerics library for the Mojo programming language.

    - [tjkessler/mojoml](https://github.com/tjkessler/mojoml)  : Linear algebra and machine learning in Mojo 🔥

    - [shivasankarka/SciJo](https://github.com/shivasankarka/SciJo)  : SciJo is a high-performance numerical computation library in Mojo, inspired by NumPy, SciPy, and Scikit-HEP. It offers efficient array operations and mathematical functions and much more for scientific computing.

## Machine Learning

  - ### Machine Learning Framework

    - [Torch-MLIR](https://github.com/llvm/torch-mlir)  : The Torch-MLIR project aims to provide first class support from the PyTorch ecosystem to the MLIR ecosystem.

    - [ONNX-MLIR](https://github.com/onnx/onnx-mlir)  : Representation and Reference Lowering of ONNX Models in MLIR Compiler Infrastructure.

    - [TPU-MLIR](https://github.com/sophgo/tpu-mlir)  : Machine learning compiler based on MLIR for Sophgo TPU.

    - [IREE](https://github.com/iree-org/iree)  : A retargetable MLIR-based machine learning compiler and runtime toolkit. [iree.dev/](http://iree.dev/)

    - [Basalt](https://github.com/basalt-org/basalt)  : A Machine Learning framework from scratch in Pure Mojo 🔥. Basalt is a stand-alone machine learning framework that leverages the power of Mojo.

    - [Endia](https://github.com/endia-org/Endia)  : Scientific Computing in Mojo 🔥. Endia is a dynamic Array library for Scientific Computing, similar to PyTorch, Numpy and JAX. [endia.vercel.app](https://endia.vercel.app/)

    - [Infermo](https://github.com/TilliFe/Infermo)  : Tensors and dynamic Neural Networks in Mojo.

    - [MojoNet](https://github.com/guna-sd/MojoNet)  : MojoNet is a ML/DL framework written in mojo🔥

    - [StijnWoestenborghs/gradi-mojo](https://github.com/StijnWoestenborghs/gradi-mojo)  : Gradient Descent in Mojo 🔥

    - [tjkessler/mojoml](https://github.com/tjkessler/mojoml)  : Linear algebra and machine learning in Mojo 🔥

    - [henrithomas/mojo-neural-net](https://github.com/henrithomas/mojo-neural-net)  : simple neural network implementation in mojo.

    - [openxla/iree](https://github.com/openxla/iree)  : IREE: Intermediate Representation Execution Environment. A retargetable MLIR-based machine learning compiler and runtime toolkit. [iree.dev/](http://iree.dev/)

  - ### Large Language Model

    - [llama2.mojo](https://github.com/tairov/llama2.mojo)  : Inference Llama 2 in one file of pure 🔥

    - [llm.mojo](https://github.com/dorjeduck/llm.mojo)  : port of Andrjey Karpathy's llm.c to Mojo.

    - [lKCaverly/mojo_gpt_from_scratch](https://github.com/KCaverly/mojo_gpt_from_scratch)  : An implementation of GPT in Mojo From Scratch.

    - [Terapines/llama3.mojo](https://github.com/Terapines/llama3.mojo)  : llama3 in mojo🔥

  - ### AI Generated Content

    - [lrmantovani10/Stable-Diffusion.mojo](https://github.com/lrmantovani10/Stable-Diffusion.mojo)  : A Mojo implementation of a smaller, Stable Diffusion-like model.

  - ### Image Recognition

    - [TENBrnak/MNIST_in_mojo](https://github.com/TENBrnak/MNIST_in_mojo)  : This repository will contain my work as I attempt to develop a neural network in pure Mojo🔥 to solve the MNIST and Fashion MNIST image recognition dataset.

  - ### Object Detection

    - [taalhaataahir0102/Mojo-Yolo](https://github.com/taalhaataahir0102/Mojo-Yolo)  : Mojo-Yolo.

## Test Framework

  - [guidorice/mojo-pytest](https://github.com/guidorice/mojo-pytest)  : Mojo test runner, pytest plugin (aka pytest-mojo).

## Command Line Interpreter

  - [thatstoasty/prism](https://github.com/thatstoasty/prism)  : Mojo CLI Library modeled after Cobra.

## Parser

  - [ZacHooper/mojo-json](https://github.com/ZacHooper/mojo-json)  : Json Parser in Mojo.

## Database

  - [sbrunk/duckdb.mojo](https://github.com/sbrunk/duckdb.mojo)  : Mojo Bindings for DuckDB.

## Date and Time

  - [mojoto/morrow.mojo](https://github.com/mojoto/morrow.mojo)  : Human-friendly date & time for Mojo 🔥

  - [maniartech/mojo-datetime](https://github.com/maniartech/mojo-datetime)  : DateTime library in pure Mojo language.

## Embedded Development

  - [YichengDWu/yoho](https://github.com/YichengDWu/yoho)  : A compiler written in Mojo 🔥 and generates RISC-V assembly.

## File Processing

  - [mzaks/mojo-csv](https://github.com/mzaks/mojo-csv)  : This library provides facilities to read and write data in CSV format according to [RFC-4180](https://www.rfc-editor.org/rfc/rfc4180)

## Image Processing

  - [Benny-Nottonson/MIL](https://github.com/https://github.com/Benny-Nottonson/MIL)  : An image library for Mojo, inspired by PIL.

  - [fnands/mimage](https://github.com/fnands/mimage)  : A library for parsing images in Mojo.

  - [f-saez/libjpeg-mojo](https://github.com/f-saez/libjpeg-mojo)  : FFI bindings for libjpeg.

## Hash Function

  - [mzaks/mojo-hash](https://github.com/mzaks/mojo-hash)  : A collection of hash functions implemented in Mojo.

## HTTP Framework

  - [saviorand/lightbug_http](https://github.com/saviorand/lightbug_http)  : Simple and fast HTTP framework for Mojo! 🔥

  - [thatstoasty/mojo-http-client](https://github.com/thatstoasty/mojo-http-client)  : Simple socket wrapper and http client for Mojo.

## TCP Framework

  - [Jensen-holm/FireTCP](https://github.com/Jensen-holm/FireTCP)  : TCP Service framework for the mojo programming language 🔥

## Web Framework

  - [igorgue/fire](https://github.com/igorgue/fire)  : Fire is a web framework written in Mojo (🔥) with some Python (🐍) magic (✨).

  - [tkruer/campfire](https://github.com/tkruer/campfire)  : A web framework for the Mojo programming language.

## Translation

  - [msaelices/py2mojo](https://github.com/msaelices/py2mojo)  : Automated Python to Mojo code translation.

## Quantitative Trading

  - [f0cii/moxt](https://github.com/f0cii/moxt)  : A high-performance trading library, written in Mojo and C++, designed to simplify quantitative trading.

## Data Storing and Processing

  - [mojo-data/arrow.mojot](https://github.com/mojo-data/arrow.mojot)  : Apache Arrow in Mojo🔥

## GUI

  - [rd4com/mojo-ui-html](https://github.com/rd4com/mojo-ui-html)  : mmediate mode GUI, HTML, CSS, Work in progress, Mojo language.

## Blogs

  - [Modular Blog](https://www.modular.com/blog)

    - [2022-04-26，The future of AI depends on Modularity](https://www.modular.com/blog/the-future-of-ai-depends-on-modularity)

    - [2023-03-23，AI’s compute fragmentation: what matrix multiplication teaches us](https://www.modular.com/blog/ais-compute-fragmentation-what-matrix-multiplication-teaches-us)

    - [2023-04-20，The world's fastest unified matrix multiplication](https://www.modular.com/blog/the-worlds-fastest-unified-matrix-multiplication)

    - [2023-05-02，A unified, extensible platform to superpower your AI](https://www.modular.com/blog/a-unified-extensible-platform-to-superpower-your-ai)

    - [2023-06-08，Do LLMs eliminate the need for programming languages?](https://www.modular.com/blog/do-llms-eliminate-the-need-for-programming-languages)

    - [2023-08-08，An easy introduction to Mojo🔥 for Python programmers](https://www.modular.com/blog/an-easy-introduction-to-mojo-for-python-programmers)

    - [2023-08-18，How Mojo🔥 gets a 35,000x speedup over Python – Part 1](https://www.modular.com/blog/how-mojo-gets-a-35-000x-speedup-over-python-part-1)

    - [2023-08-24，We’ve raised $100M to fix AI infrastructure for the world's developers](https://www.modular.com/blog/weve-raised-100m-to-fix-ai-infrastructure-for-the-worlds-developers)

    - [2023-08-28，How Mojo🔥 gets a 35,000x speedup over Python – Part 2](https://www.modular.com/blog/how-mojo-gets-a-35-000x-speedup-over-python-part-2)

    - [2023-09-06，Mojo🔥 - A journey to 68,000x speedup over Python - Part 3](https://www.modular.com/blog/mojo-a-journey-to-68-000x-speedup-over-python-part-3)

    - [2023-09-07，Mojo🔥 - It’s finally here!](https://www.modular.com/blog/mojo-its-finally-here)

    - [2023-10-02，Using Mojo🔥 with Python🐍](https://www.modular.com/blog/using-mojo-with-python)

    - [2023-10-13，Community Spotlight: How I built llama2.🔥 by Aydyn Tairov](https://www.modular.com/blog/community-spotlight-how-i-built-llama2-by-aydyn-tairov)

    - [2023-10-15，Mojo 🔥 - A systems programming language presented at LLVM 2023](https://www.modular.com/blog/mojo-llvm-2023)

    - [2023-10-19，Mojo🔥 is now available on Mac](https://www.modular.com/blog/mojo-is-now-available-on-mac)

    - [2023-11-14，What’s new in Mojo SDK v0.5?](https://www.modular.com/blog/whats-new-in-mojo-sdk-v0-5)

    - [2023-11-20，Implementing NumPy style matrix slicing in Mojo🔥](https://www.modular.com/blog/implementing-numpy-style-matrix-slicing-in-mojo)

    - [2023-11-21，ModCon Mojo 🔥 Contest](https://www.modular.com/blog/modcon-mojo-contest)

    - [2023-11-22，ModCon 2023 sessions you don’t want to miss!](https://www.modular.com/blog/modcon-2023-sessions-you-dont-want-to-miss)

    - [2023-12-03，Mojo 🔥 Traits Have Arrived!](https://www.modular.com/blog/mojo-traits-have-arrived)

    - [2023-12-04，Key announcements from ModCon 2023](https://www.modular.com/blog/key-announcements-from-modcon-2023)

    - [2024-01-23，Mojo 🔥 lightning talk ⚡️ one language for all AI programming!](https://www.modular.com/blog/mojo-lightning-talk)

    - [2024-01-25，Mojo🔥 SDK v0.7 now available for download!](https://www.modular.com/blog/mojo-sdk-v0-7-now-available-for-download)

    - [2024-01-29，What is loop unrolling? How you can speed up Mojo🔥 code with @unroll](https://www.modular.com/blog/what-is-loop-unrolling-how-you-can-speed-up-mojo)

    - [2024-02-02，Community Spotlight: Outperforming Rust ⚙️ DNA sequence parsing benchmarks by 50% with Mojo 🔥](https://www.modular.com/blog/outperforming-rust-benchmarks-with-mojo)

    - [2024-02-12，Mojo vs. Rust: is Mojo 🔥 faster than Rust 🦀 ?](https://www.modular.com/blog/mojo-vs-rust-is-mojo-faster-than-rust)

    - [2024-02-15，Mojo🔥 ♥️ Python: Calculating and plotting a Valentine’s day ♥️ using Mojo and Python](https://www.modular.com/blog/mojo-python-calculating-and-plotting-a-valentines-day-using-mojo-and-python)

    - [2024-02-26，What are dunder methods? A guide in Mojo🔥](https://www.modular.com/blog/what-are-dunder-methods-a-guide-in-mojo)

    - [2024-02-29，MAX is here! What does that mean for Mojo🔥?](https://www.modular.com/blog/max-is-here-what-does-that-mean-for-mojo)

    - [2024-03-14，Mojo🔥 ❤️ Pi 🥧: Approximating Pi with Mojo🔥 using Monte Carlo methods](https://www.modular.com/blog/mojo-pi-approximating-pi-with-mojo-using-monte-carlo-methods)

    - [2024-03-28，The Next Big Step in Mojo🔥 Open Source](https://www.modular.com/blog/the-next-big-step-in-mojo-open-source)

    - [2024-04-02，What’s new in Mojo 24.2: Mojo Nightly, Enhanced Python Interop, OSS stdlib and more](https://www.modular.com/blog/whats-new-in-mojo-24-2-mojo-nightly-enhanced-python-interop-oss-stdlib-and-more)

    - [2024-04-08，How to Contribute to Mojo Standard Library: A Step-by-Step Guide](https://www.modular.com/blog/how-to-contribute-to-mojo-standard-library-a-step-by-step-guide)

    - [2024-04-10，Row-major vs. column-major matrices: a performance analysis in Mojo and NumPy](https://www.modular.com/blog/row-major-vs-column-major-matrices-a-performance-analysis-in-mojo-and-numpy)

    - [2024-05-02，What’s New in Mojo 24.3: Community Contributions, Pythonic Collections and Core Language Enhancements](https://www.modular.com/blog/whats-new-in-mojo-24-3-community-contributions-pythonic-collections-and-core-language-enhancements)

    - [2024-05-08，Developer Voices: Deep Dive with Chris Lattner on Mojo](https://www.modular.com/blog/developer-voices-deep-dive-with-chris-lattner-on-mojo)

    - [2024-05-15，What Does Joe Pamer, AI and PL expert, Want From Mojo?](https://www.modular.com/blog/meet-joe-pamer-mojo-engineering-lead)

    - [2024-05-20，Fast⚡ K-Means Clustering in Mojo🔥: Guide to Porting Python to Mojo🔥 for Accelerated K-Means Clustering](https://www.modular.com/blog/fast-k-means-clustering-in-mojo-guide-to-porting-python-to-mojo-for-accelerated-k-means-clusteringuiu)

    - [2024-05-29，What Ownership is Really About: A Mental Model Approach](https://www.modular.com/blog/what-ownership-is-really-about-a-mental-model-approach)

    - [2024-06-04，Deep Dive into Ownership in Mojo](https://www.modular.com/blog/deep-dive-into-ownership-in-mojo)

    - [2024-06-07，MAX 24.4 - Introducing Quantization APIs and MAX on macOS](https://www.modular.com/blog/max-24-4-introducing-quantization-apis-and-max-on-macos)

    - [2024-06-17，What’s New in Mojo 24.4? Improved collections, new traits, os module features and core language enhancements](https://www.modular.com/blog/whats-new-in-mojo-24-4-improved-collections-new-traits-os-module-features-and-core-language-enhancements)

    - [2024-06-25，What's New in MAX 24.4? MAX on MacOS, Fast Local Llama3, Native Quantization and GGUF Support](https://www.modular.com/blog/whats-new-in-max-24-4-max-on-macos-fast-local-llama3-native-quantization-and-gguf-support)

    - [2024-07-03，A brief guide to the Mojo n-body example](https://www.modular.com/blog/a-brief-guide-to-the-mojo-n-body-example)

    - [2024-07-16，Debugging in Mojo🔥](https://www.modular.com/blog/debugging-in-mojo)

  - 微信公众号「Mojo语言」

    - [2024-03-03，LLVM之父发起的Mojo比Rust速度更快吗？](https://mp.weixin.qq.com/s/5gQTfNFciwhwdBywpFmr4w)

  - 微信公众号「生信杂货铺」

    - [2024-05-10，Mojo 学习 —— 环境配置](https://mp.weixin.qq.com/s/8gxJOLjXTTIifPbQBwH8XA)

    - [2024-05-11，Mojo 学习 —— 基本语法](https://mp.weixin.qq.com/s/XntAnR6o1xLXq3T8js-FZA)

    - [2024-05-12，Mojo 学习 —— 数据类型](https://mp.weixin.qq.com/s/emGVEadLQEWhUy9s40p66w)

    - [2024-05-13，Mojo 学习 —— 函数](https://mp.weixin.qq.com/s/rmRlnciuV1Iyfycw5K2IBg)

    - [2024-05-14，Mojo 学习 —— 结构体](https://mp.weixin.qq.com/s/A_P_nUge7gWTpS0IGZ7ahA)

    - [2024-05-15，Mojo 学习 —— 值的所有权](https://mp.weixin.qq.com/s/GiNJVoW9cuXinGiooYr9cg)

    - [2024-05-16，Mojo 学习 —— 值的生命周期](https://mp.weixin.qq.com/s/EQRutjvZLeMmQbMb1ZyF2g)

    - [2024-05-17，Mojo 学习 —— 特性（trait）](https://mp.weixin.qq.com/s/TWDWBrHFbBV9CpuQOuBjZg)

    - [2024-05-18，Mojo 学习 —— 参数化：编译时元编程](https://mp.weixin.qq.com/s/GXr3Iej8Rv8hybeLiGFOpA)

    - [2024-05-19，Mojo 学习 —— 装饰器](https://mp.weixin.qq.com/s/ujzyiSVWgGAHS3QgCmrHNg)

    - [2024-05-20，Mojo 学习 —— 与 Python 交互](https://mp.weixin.qq.com/s/ntX0RGNUJl5uNgpHKaIH_g)

    - [2024-05-21，Mojo 学习 —— 内置结构与函数](https://mp.weixin.qq.com/s/-uRhizTz7Jfd6HLX33xL6w)

    - [2024-05-22，Mojo 学习 —— SIMD](https://mp.weixin.qq.com/s/Jv6KucJgv89c8J5WaES0sw)

    - [2024-05-23，Mojo 学习 —— 指针](https://mp.weixin.qq.com/s/OrM-dRITMlkCQAcx_bLYeQ)

    - [2024-05-24，Mojo 学习 —— 并行化](https://mp.weixin.qq.com/s/JznAX5Xye2gdXAaKP5dIEQ)

  - 微信公众号「GiantPandaCV」

    - [2023-06-25，MLIR_对自定义IR Dialect编写bufferization pass](https://mp.weixin.qq.com/s/3aHwYDkI9K3u-10v6-9iVA)

  - 微信公众号「NeuralTalk」

    - [2023-06-16，SIMD 指令集与数据并行程序](https://mp.weixin.qq.com/s/dgTtEY5NZh-npQ6KN2WoaA)

## Videos

  - [Modular](https://www.youtube.com/@modularinc)

    - [2023-05-03，Product Launch 2023 Keynote](https://www.youtube.com/watch?v=-3Kf2ZZU-dg)

    - [2023-05-03，Modular Product Keynote in 121 seconds](https://www.youtube.com/watch?v=LaWTkXruke0)

    - [2023-08-26，Speeding up Python code with Mojo🔥: Mandelbrot example](https://www.youtube.com/watch?v=wFMB0VSH51M)

    - [2023-09-02，Modular Community Livestream - 6 popular questions and answers](https://www.youtube.com/watch?v=mQh9es5gfpo)

    - [2023-10-07，Introduction to Tensors in Mojo🔥](https://www.youtube.com/watch?v=3OWkXNdkx8E)

    - [2023-10-10，Cross Platform Mojo App with Conda, PyTorch and Matplotlib](https://www.youtube.com/watch?v=bmpjT0T4IDY)

    - [2023-12-05，ModCon23 Keynote Livestream](https://www.youtube.com/watch?v=VKxNGFhpYQc)

    - [2024-05-13，Mojo🔥: a deep dive on ownership with Chris Lattner](https://www.youtube.com/watch?v=9ag0fPMmYPQ)

    - [2024-05-24，Mojo Community Meeting #1](https://www.youtube.com/watch?v=uIG9q9foIw0)

    - [2024-06-08，Mojo Community Meeting #2](https://www.youtube.com/watch?v=3FKSlhZNdL0)

    - [2024-06-18，Mojo Community Meeting #3](https://www.youtube.com/watch?v=onrRbJ6DeYg)

    - [2024-07-23，Mojo Community Meeting #4](https://www.youtube.com/watch?v=_QVs626Vn2k)

    - [2024-07-30，Mojo Community Meeting #5](https://www.youtube.com/watch?v=1T-MBC9k99M)

    - [2024-08-15，MAX + Mojo Community Meetings #6](https://www.youtube.com/watch?v=6huytcgQgk8)

  - [Developer Voices](https://www.youtube.com/@DeveloperVoices)

    - [2024-02-10，Mojo Lang - Tomorrow's High Performance Python? (with Chris Lattner)](https://www.youtube.com/watch?v=JRcXUuQYR90)

  - [ThePrimeTime](https://www.youtube.com/@ThePrimeTimeagen)

    - [2024-02-10，Mojo Is FASTER Than Rust](https://www.youtube.com/watch?v=kmmqHV26Ukg)

    - [2024-02-16，[UPDATE] Mojo Is Faster Than Rust - Mojo Explains More](https://www.youtube.com/watch?v=MDblUyz0PtQ)

## Jobs and Interview

  - 微信公众号「HelloGCC」

    - [2024-03-08，一大波前沿编译器岗位来袭，Dataflow, Mojo, MLIR, CIRCT, ClangIR, LLVM...](https://mp.weixin.qq.com/s/rntOFBKKFOdmt5arGzsvFA)