The State of M1 Macs for Developers — Setup Guides and Benchmarking

Welcome to the 10th edition of Coffee Bytes, a daily digest by Better Programming.

Back in November 2020, Apple unveiled its in-house ARM-based chips for the Mac. One year and two versions later, the future of Apple Silicon looks even more promising with the transition occurring smoothly.

If you’re looking to get your M1 Mac ready for daily workflow or need some inspiration to migrate to the beast, we’ve got a list of configurations guides, benchmark testing posts, and experiments by developers to let you make the switch.

Photo by Clayton Malquist on Unsplash

• For history buffs, when M1 MacBook was first launched, Docker was not supported. Andreas Heissenberger’s guide had depicted the issues along with intermediate solutions.
• Apple’s New M1 Chip is a Machine Learning Beast — Daniel Bourke did a thorough analysis by speed testing a (nearly) top-spec Intel-based 16-inch MacBook Pro versus the new Apple silicon MacBook Air and 13-inch MacBook Pro. While experimenting with the CreateML app for model training, the M1 Mac won hands down.
• Benchmark M1 vs Xeon vs Core i5 vs K80 and T4 — Fabrice Daniel compares Apple Silicon M1 CPU and GPU performances to high-end configurations on MLP, CNN, and LSTM models.
• Next up, Martin Albrecht discusses the problems, findings, and workarounds while getting Ruby programs up and running on the Apple Silicon M1 Macs.
• Read Elye’s first view for Android development on the Apple M1 chip device, the issues he faced while setting up Android emulators, and tips to speed up Android compilation.
• Since then, M1 Pro for Android engineers has come a long way. Gabriel Peal showcases the performance improvements succinctly.
• Wait! What about SonarQube ? Catalin Patrascu’s how-to guide walks us through the setup of SonarQube with Flutter using Docker on Apple Silicon Mac.
• At the same time, David J Harding’s developing a React Native app on an M1 Mac without Rosetta guide covers the other spectrum of the cross-platform ecosystem.
• Is your existing x86–64 machine built using Vagrant and Virtualbox no longer running? Head over to Running Virtual Machines Under Vagrant on the New Mac M1. A guide by James Cundle to find your working VM alternative.
• Jason Sturges offers us a guide for setting up game development, coding, and creative environment on a new MacBook Pro with M1 architecture.
• Head over to Matt Wang’s guide to setup Kubernetes on Apple M1 using minikube.
• Data scientists would love these guides — 1) Install XGBoost and LightGBM on Apple M1 Macs. 2) Installing Tensorflow on Apple M1 With the New Metal Plugin and Install PyTorch on Apple M1-series by Nikos Kafritsas
• Need more? Dario Radečić gave us the ultimate data science comparison between M1 vs. i9–9880H — a performance comparison with synthetic benchmarks, Python, Numpy, Pandas, and Scikit Learn.
• What if you’re bored with sequential programming and want to try out parallel computing? Worry not! Mihail-Iulian Pleșa has a guide for you to integrate Open MPI with CLion for Apple M1.
• Lastly, Tate Galbraith jotted down 5 Developer Tweaks For New M1 Macs. It also includes general tips to integrate your existing workflow into the new platform.

That’s all. Thanks for reading.