M1 Pro First Impressions: Core Management and CPU Performance

• xcode-hardware-performance

  2 1,153 2.6

  Discontinued Results from running Xcode on a non-trivial open source project using various Macs

• aws-graviton-getting-started

  62 819 8.5 Python

  Helping developers to use AWS Graviton2 and Graviton3 processors which power the 6th and 7th generation of Amazon EC2 instances (C6g[d], M6g[d], R6g[d], T4g, X2gd, C6gn, I4g, Im4gn, Is4gen, G5g, C7g[d][n], M7g[d], R7g[d]).

  

I know that AWS already have their own ARM chips: https://aws.amazon.com/ec2/graviton/. I don't know about chips enough to understand how large is the gap between AWS and Apple when it comes to designing chips though.

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• Amethyst

  148 14,194 6.5 Swift

  Automatic tiling window manager for macOS à la xmonad.

• rust-crc32fast

  4 231 4.8 Rust

  Fast, SIMD-accelerated CRC32 (IEEE) checksum computation in Rust

• Rectangle

  724 24,591 8.5 Swift

  Move and resize windows on macOS with keyboard shortcuts and snap areas

You can run linux on it if you want, for most productivity related issues there are open source tools like [Rectangle](https://rectangleapp.com) for what you're talking about.

other tools like the Dash app are also amazing tools to speed up the development process. It will take some getting used to moving from Windows and to a far lesser extent linux, however with the right tools for the job you will end up being more productive and less frustrated. Especially compared to Windows.

Unless I need something that specifically only runs on Windows, I would use Mac/Linux over it any day of the week. For productivity it's Mac > Linux >>> Windows for me.

• mmperf

  2 121 4.3 C++

  MatMul Performance Benchmarks for a Single CPU Core comparing both hand engineered and codegen kernels.

  

Could you give me a benchmark in particular? Or maybe this one works: https://github.com/mmperf/mmperf. I'll run it in an hour.

• PurefunctionPipelineDataflow

  172 439 7.4

  My Blog: The Math-based Grand Unified Programming Theory: The Pure Function Pipeline Data Flow with principle-based Warehouse/Workshop Model

Apple M1 just follow my "Warehouse/Workshop Model".

Its mathematical prototype is the simple, classic, vivid, and widely used in social production practice, elementary school mathematics "water input/output of the pool" as a mathematical prototype, Therefore, it is scientific.

The "von Neumann architecture" used by computers now has no mathematical model support. So it cannot prove its scientificity.

My theory rebuilt the theoretical foundation of the IT industry, The IT industry is fundamentally associated with mathematics. Solved the most fundamental and core major problems in the IT industry.

Therefore, my "warehouse/workshop model" will surely replace the "von Neumann architecture" and become the first architecture in the computer field, and it is the first architecture to achieve a unified software and hardware.

Software and hardware are factories that manufacture data, so they have the same "warehouse/workshop model" and management methods as the manufacturing industry.

In the IT field, only it and binary system fully comply with these 5 aesthetics: Simplicity, Unity, order, symmetry and definiteness.

It has a wide range of applications, from SOC to supercomputer, from software to hardware, from stand-alone to network, from application layer to system layer, from single thread to distributed, from general programming to explainable AI, from manufacturing industry to IT industry, from energy to finance, from the missile's "Fire-and-Forget" technology to Boeing aircraft pulse production line technology, from myth to Transformers.

Link:

The Grand Unified Programming Theory: The Pure Function Pipeline Data Flow with Principle-based Warehouse/Workshop Model

https://github.com/linpengcheng/PurefunctionPipelineDataflow

Why my "warehouse/workshop model" can achieve high performance and low power consumption (take Apple M1 chip, Intel AVX-512, Qualcomm as examples):

https://github.com/linpengcheng/PurefunctionPipelineDataflow...

• SaaSHub

  www.saashub.com featured

  SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

  

• performance_results

  1 24 4.0 Roff

  performance results/benchmarks for a variety of machines

https://github.com/deater/performance_results

• flops

  2 27 10.0 C

  Tiny cpu benchmark (by brianolson)

So a friend that has a M1 did this test: https://github.com/brianolson/flops/blob/master/flops.c

And the 5nm M1 has ~2.5Gflops/W which is not a huge increase compared to the 28nm Pi 4 at 2Gflops/W.

No-moores law in effect. Game Over!

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