I've updated the pages comparing the new Apple Silicon machines with those with the older Intel chips https://www.macinchem.org/reviews/MacBooks/m1macbookpromax.php. In addition to the MacBook Pro M1 Max I've now added the M2 MacBook Air.

 

I'm slowly working through a variety of cheminformatics toolkits and computational chemistry applications, I'm trying to run some "real world" workflows so you can see what kind of performance improvement you might expect.

The index page is here https://www.macinchem.org/reviews/MacBooks/m1macbookpromax.php and I'll update it as a test more applications.

 

So the Apple event revealed the new Apple Mac Studio, a double hight Mac mini, when combined with the new M1 Ultra chip this small enclosure appears to deliver really impressive performance.

The M1 Ultra is an evolution of the M1max chip that uses "UltraFusion" technology to fuse two M1 Max chips together, resulting in a huge processor that offers 16 high-performance CPU cores, 4 efficiency cores, a 48- or 64-core integrated GPU, and support for up to 128GB of RAM, 800GB/s of memory bandwidth and a 32-core Neural Engine.

Whilst Apple gave the usual performance tests based on video editing I'm not sure they give a realistic measure of performance for scientific applications.

I've been looking at a variety of different application/toolkits/python scripts etc. on my MacBook Pro M1 max here , and if anyone has a chance to test scientific software on the M1Ultra I'd be happy to include the results.

 

AlphaFold2 is an artificial intelligence (AI) program developed by Alphabets's/Google's DeepMind which performs predictions of protein structure. Despite the name AlphaFold2 does not actually predict the folding mechanism instead it predicts the final 3D structure of a protein from the protein sequence DOI.

Source code for the AlphaFold model, trained weights and inference script are available under an open-source license at https://github.com/deepmind/alphafold.

I've compiled step by step instructions for installing Alphafold2 on a MacBook Pro M1 max here https://www.macinchem.org/reviews/alphafold/installalphafold2.php.

Many thanks to Yoshitaka Moriwaki for help.

 

As some of you may have seen I've started the comparison of my new MacBook Pro Apple M1 max with my old Intel MacBook.

I'm slowly working through a variety of cheminformatics toolkits and computational chemistry applications, I'm trying to run some "real world" workflows so you can see what kind of performance improvement you might expect.

The index page is here https://www.macinchem.org/reviews/MacBooks/m1macbookpromax.php and I'll update it as a test more applications

When possible I've used the latest builds for the M1 arm architecture. Both machines were connected to power and had no other applications running. To date I've looked at the following.

• RDKit
• OpenBabel
• Jupyter
• SMINA
• Vortex
• MOE
• PyMOL

More to come.

 

The new MacBook Pros are out and they look fantastic, powered by M1Pro or M1Max chips they offer outstanding performance and retain low power consumption. As expected, Apple has added a HDMI port, and an SD card slot, AND has brought back MagSafe.

Details on the chip design

You can also watch the promotional video here