Modeller written in Fortran90 has been ported to Apple Silicon
They used the gfortran that's part of the gcc homebrew package (https://brew.sh/). They see about a 20% performance improvement with gfortran-10 on a 2020 Mac Mini (M1) compared to Intel Fortran on a 2018 Mac Mini (Intel).
MODELLER is used for homology or comparative modeling of protein three-dimensional structures. The user provides an alignment of a sequence to be modeled with known related structures and MODELLER automatically calculates a model containing all non-hydrogen atoms. MODELLER implements comparative protein structure modeling by satisfaction of spatial restraints, and can perform many additional tasks, including de novo modeling of loops in protein structures, optimization of various models of protein structure with respect to a flexibly defined objective function, multiple alignment of protein sequences and/or structures, clustering, searching of sequence databases, comparison of protein structures, etc.
If you are using the Homebrew package manager, you can install Modeller on recent Macs (either Intel or Apple Silicon, M1) by simply running
brew tap salilab/salilab brew install modeller
OpenMM is a toolkit for molecular simulation using high performance GPU code.
This is a patch release. It contains a small number of bug fixes, as well as changes to enable two significant additions to the supported platforms.
First, this release provides preliminary support for ARM based Macs. The support has not been extensively tested and should be treated as beta quality. Please try it out and let us know if you encounter any bugs while using it.
Second, we are now providing conda packages for use with Pypy. This is an alternate Python interpreter that uses just-in-time compilation to provide much faster execution than CPython. You can create a conda environment that uses Pypy with the command
conda create -c conda-forge --name pypy pypy
Docker is now available for M1 machines
The release note can be found here https://docs.docker.com/docker-for-mac/release-notes/
and you download it here.
The very popular bioinformatics tool MacVector 18.1 is now available to download. MacVector 18.1 is a Universal Binary application, which means it runs natively on both Apple Silicon M1 Macs and Intel Macs. MacVector 18.1 matches the “Big Sur” look and feel. …and for the first time in many, many years the MacVector icon has changed to match the square look of macOS Big Sur icons.
We ran some benchmarks to see how much faster MacVector now runs on an Apple Silicon MacBook Pro. We compared this against MacVector 18.0, which runs using Rosetta2 emulation. In some cases you can see that the native Apple Silcon MacVector 18.1 runs 200% faster than the emulated MacVector 18.0.
The full CSD software portfolio, including Mercury, ConQuest, Mogul, GOLD, CSD-CrossMiner, the CSD Python API and other components, has now been upgraded and tested for compatibility with Big Sur. We are pleased to report that the newly available 2020.3.1 CSD Release (only available on macOS) is fully supported on macOS Big Sur at point of release, both for Intel-based macs, as well as the newer M1 Apple silicon based macs. At this point we are aware of just two specific known issues for the newer silicon hardware machines:
- The POV-Ray integration in Mercury for high-resolution graphics generation does not work on M1 Apple silicon based macs
- The Aromatics Analyser component in the CSD-Materials menu of Mercury does not work on M1 Apple silicon based macs We expect that these final remaining issues will be addressed in the next CSD software release.
Full details are here https://www.ccdc.cam.ac.uk/solutions/whats-new/.
More details on scientific applications under Big Sur are here https://www.macinchem.org/blog/files/1fd84c61d3f91608c1b9c413c8064cd4-2692.php
We are just starting to see a few benchmarks on the new Apple M1 chip using scientific applications.
This blog post looks like it will be really interesting to follow.
In this post, which I expect will be the first in a series, I’ll share the code that got me running with a basic Python 3.9, scipy, and matplotlib environment. However, I immediately took it further, getting a working – and quite well-performing – installations of the Atomic Simulation Environment (ASE), used for building, manipulating and visualizing atomistic structure files, as well as a parallel installation of the density functional theory code GPAW.
not even having 10 high-performance Xeon cores in the iMac Pro instead of only 4 high-performance M1 cores in the MacBook Pro brought the two systems to parity: the M1 MacBook Pro handily wins this comparison.
Homebrew has been updated
Apple Silicon is now officially supported for installations in /opt/homebrew. formulae.brew.sh formula pages indicate for which platforms bottles (binary packages) are provided and therefore whether they are supported by Homebrew. Homebrew doesn’t (yet) provide bottles for all packages on Apple Silicon that we do on Intel x8664 but we welcome your help in doing so. Rosetta 2 on Apple Silicon still provides support for Intel x8664 in /usr/local.
A lot of people have been asking me about running data analysis on the new laptops with M1 chips. It looks like we are starting to see a few benchmarks appearing.
A recent blog post Are The New M1 Macbooks Any Good for Data Science? Let’s Find Out would suggest that the performance of the M1chip continues to impress.
Whilst all benchmarks come with caveats, some use "native" installations others require Rosetta
Python is approximately three times faster when run natively on a new M1 chip, Numpy looks to be slightly slower, Pandas is twice as fast, SciKit-Learn is twice as fast.
Instructions for installing TensorFlow 2.4 on Apple Silicon M1: installation under Conda environment have also been reported.
PyCharm, JetBrains’ IDE for Python development, now supports Apple Silicon M1 processors.
The ARM OSX Migration seems to be quite active :-)
And here it is
OpenMM is now available on condaforge for osx-64 to support new Apple hardware based on the Mac M1 chip!
conda install -c conda-forge openmm
I'd be really interested in hearing about any benchmarking activities.
Analyzing the runtime, energy usage, and performance of Tensorflow training on a M1 Mac Mini and Nvidia V100
An interesting comparison of Apple Intel and M1 chips machines with Nvidia 100 when using Tensorflow.
We ran a sweep of 8 different configurations of our training script and show that the Apple M1 offers impressive performance within reach of much more expensive and less energy efficient accelerators such as the Nvidia V100 for smaller architectures and datasets.
Code is available on Colab https://colab.research.google.com/drive/1RvZBpzJRW9MNPWQ2rZG8HIyHJbaCwnTI.
They also include tips on setting up a Mac mini to run Tensorflow.
Only initial results on modest data sets, will be interesting to see the performance when Apple releases more Pro hardware.
A technical but still very accessible (15 min) analysis of the latest Apple M1 chip. Well worth spending a coffee break viewing.
General Issues with Big Sur
If you want an overview of Big Sur I'd recommend the excellent arstechnica review.
Apple has officially confirmed that the following Macs are compatible with Big Sur.
- MacBook (2015 or newer)
- MacBook Air (2013 or newer)
- MacBook Pro (Late 2013 or newer)
- Mac mini (2014 or newer)
- iMac (2014 or newer)
- iMac Pro (2017)
- Mac Pro (2013 and later)
In addition there is issue of the new Apple Silicon Macs with the new Apple M1 chip, if there is specific information about the new machines I've included it.
I've contacted all developers I know and their responses to date are shown below.
4-Peaks no known issues
Absoft Absoft Pro Fortran 2021 For macOS and OS X Fully compatible with macOS Big Sur (11.0)
alvaDesc We tested all our products and all of them work properly on MacOS Big Sur.
Amsterdam Modeling Suite As we only just finished our 2020 release our developers didn't dare switching to Big Sur yet. I can try on my own macbook shortly.
Anaconda seems to be working fine.
APE make sure you download the 64-bit version
Avogadro Been running Big Sur betas for a while - everything works. The next beta of Avogadro v2 will have some interface tweaks that are more noticeable on Big Sur (e.g., warning dialogs changed to be Mac-native). Don't yet have universal binaries, but working on it for Open Babel and Avogadro v2 betas (e.g. 1.94). Should still work fine on Apple Silicon computers.
Brainsight macOS 11 Big Sur is coming out very soon, but do not upgrade your Mac yet, because Brainsight is not yet compatible with Big Sur
ChemAxon Most of our software in general requires Java, so as long as the appropriate Java version is installed, there should be no problem.
ChemDraw current version products (ChemDraw Professional 22.214.171.124 and ChemDraw Prime 126.96.36.199) supported with Mac OSX Catalina (v20.0 qualified with Mac OS 11.0 Beta)
ChemDoodle “The latest versions of ChemDoodle 2D (v11) and ChemDoodle 3D (v6) are fully supported on macOS Big Sur (macOS 10.16/11.0) and there are no known issues. In addition to supporting the operating system update, ARM based Macs (like those just released with the new Apple Silicon chip) are also fully supported for ChemDoodle 2D and ChemDoodle 3D with no known issues."
Conquest and Mercury from CCDC The full CSD software portfolio, including Mercury, ConQuest, Mogul, GOLD, CSD-CrossMiner, the CSD Python API and other components, has been tested and is not currently compatible with macOS Big Sur. Please note that our upcoming 2020.3 CSD Release will not be compatible with macOS Big Sur at point of release. We are working hard on a series of improvements to make our software portfolio compatible and fully supported, which we will make available to users as an update as soon as possible. In the meantime, a number of enhancements have been made to our products to simplify the configuration of and support specifically on macOS platforms. Examples are the removal of XQuartz as a dependency and removal of the need to run an X windows display for full use of the CSD Python API. These enhancements will be incorporated in future CSD software releases."
Cresset testing underway
CrystalMaker Works swimmingly! We’ve tested all our software on Big Sur - including a machine with Apple Silicon - and are happy to confirm full compatibility for CrystalMaker 10.5.5, SingleCrystal 4.1.0 and CrystalDiffract 6.8.5. Free updates to CrystalMaker 10.5.5 and SingleCrystal 4.1.0 were released yesterday morning and are recommended for anyone using “Big Sur”.
We are also very-pleased to announce the immediate availability of CrystalMaker 10.6 for Mac, SingleCrystal 4.1 and CrystalDiffract 10.9 for Apple Silicon: these are Universal Binaries and provide 100% native performance on the new Apple Silicon Macs, as well as 100% native performance on Intel.
As one of the vanishingly-few Mac science developers left, we’re proud of our reputation of developing genuine, native Mac apps. We’ve been doing this for over 25 years now and this is our fourth Mac hardware platform! (we’ve gone from Motorola 68K to PowerPC to Intel and now to Apple Silicon).
CYLView 1.0 does not work under Catalina.
DataWarrior Seems to be working fine.
Delta We are working on an update for Delta and will post it as soon as it is available.
DEVONagent fine under Big Sur on Intel, not tested on Apple Silicon.
DEVONthink fine under Big Sur on Intel, not tested on Apple Silicon.
Elemental Fine under Big Sur and on Apple Silicon
EndNote We are in the process of testing and we will be updating our Compatibility page once our testing is complete. Users report no issues on Intel.
EnzymeX no issues reported
EverNote is compatible with Big Sur
Findings no issues reported
Gaussaian As far as we can tell so far, both of our current releases, Gaussian 16 rev. C.01 and GaussView 6.1.1 for macOS 64-bit Intel CPUs, run normally on macOS Big Sur. We do not have any reports of problems so far. We do not have a native port for Apple Silicon chips for either G16 or GaussView 6. However, for now, both of the Intel binaries that I mentioned above should run on Apple Silicon using Rosetta 2. We have not done full certification on the Apple Silicon at this point but Apple claims that Rosetta 2 should be capable of handling running existing binaries for Intel chips.
Highlights The PDF Reader for Research, updated for Big Sur with version 2020.3. Big Sur also fixes an annoying issue from PDFKit on Catalina where superscript text (e.g. citations) would break text selection.
Homebrew For most seems to work fine, remember to reinstall Xcode command line tools.
All the ICM products are compatible with Big Sur:
Other products that are compatible include:
Igor Pro Igor Pro 8.04 is the first version of Igor that is notarized and includes notarized WaveMetrics XOPs. We therefore recommend that you run Igor Pro 8.04 if you are using macOS 10.15 or macOS 11.0.
KNIME We are testing the upcoming version 4.3 of KNIME Analytics Platform against Big Sur and plan to have it supported by the time we do that release in the first week of December.
Manuscripts no issues reported
Matlab MATLAB is compatible with macOS 11 (Big Sur) from release R2020b onwards, support for Apple Silicon is in development
Mendeley no issues reported
Microsoft Office Microsoft has announced that Office 365 is ready for Big Sur - Apple Silicon M1 Macs will use Rosetta 2 for now
Mnova The current version of Mnova LiteCDE is compatible with MacOS Big Sur
NAG Fortran compiler Fortran compiler for Apple Silicon Macs now available to download
MOE Our initial tests showed no issues with this version.
ODYSSEY Molecular Explorer version 6 looks good.
Papers no issues reported
Parallels Parallels 16 is ready for Big Sur. Older Parallels Desktop versions only partially support working on macOS Big Sur due to technical reasons may experience issues depending on the configuration.
pro Fit pro Fit 7 is now at version 7.0.18, supporting dark mode, Catalina, and Big Sur.
PYMOL On Intel Macs with macOS 11, PyMOL works fine, no known issues. We have not tested Apple Silicon (M1) yet.
Python Python 2.7 is no longer included - use Python 3 instead Python works fine on Apple Silicon and is "mad fast!".
QMForge 2.4 does not support Big Sur yet
R The front page of a CRAN site has a link ‘Download R for (Mac) OS X’. Click on that, then download the file R-4.0.3.pkg and install it. This runs on macOS 10.13 and later on Intel CPU20 (High Sierra, Mojave, Catalina, Big Sur, …).
RDKit All seems fine (Note: -Python 2.7 is no longer supported - use Python 3 instead)
Samson SAMSON 2020 R3 (the latest release) works on Big Sur.
Schrodinger Upgrading to macOS 11 will cause existing Schrödinger Suite releases to fail to run. We are hard at work to address this incompatibility and expect to extend support to macOS 11 in an upcoming Schrödinger Suite release
SeeSAR now updated to support Big Sur.
Sketch With version 70 release, we’re excited to introduce a UI redesign that fits right in with the new macOS Big Sur design language. It’s the same Sketch you know and love, but with every detail reconsidered — from a full-height sidebar, to a refreshed Inspector, and all-new iconography throughout the app.
Spartan There are a few interface issues, tab highlighting on selection is unreliable, not a showstopper but irritating.
SPSS The current release IBM SPSS Statistics 27.0.1 and the current IBM SPSS Statistics Subscription release build 188.8.131.52.1447 will run on MAC OSX 11 Big Sur in translation mode.
Stardrop We haven't yet completed a full test cycle, but we have not seen any issues and don't anticipate any.
Swiss-PdbViewer Swiss-PdbViewer is a 32 bits application and will * NOT * run.
TensorFlow and TensorFlow Addons This pre-release delivers hardware-accelerated TensorFlow and TensorFlow Addons for macOS 11.0+. Native hardware acceleration is supported on Macs with M1 and Intel-based Macs through Apple’s ML Compute framework.
UCSF ChimeraX works on 10.14, 10.15, and 11.0 (Big Sur).
VMD there interface issues under Big Sur
VMWare In preparation for the next major version of macOS 11.0 Big Sur, VMware has made full use of Apple’s hypervisor and other APIs, removing the need for kernel extensions and supporting macOS 11 as both host and guest.
Vortex Vortex works perfectly on Intel Macs under Big Sur, and on Apple Silicon
Wizard In general works fine, some issue with older work books.
Xcode need to update to latest version. Remember to reinstall command line tools
I’ll add more updates later, feel free to contact me and thanks for the comments to date.
Last update 17 January 2021