Apple's new ARM CPUs vs, classic x86 for physics?

In summary, the author is looking to replace their computer and is considering two options, a Mac or a Windows laptop. They note that the Macs are compatible with a few software titles, but the Windows laptops are not compatible with some titles. They recommend looking at what the price of an M1 Mac would get you in desktop hardware with as much screen real estate as you can afford.
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Dex_
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TL;DR Summary
ARM vs x86. Which is more compatible with Physics software?
Hi it's my first post here!
I'm in my second year of my degree and looking to replace my computer. The new M-series chips seem like a better deal, however I am nervous that some software that might not be compatible with the ARM architecture. For more context on my workflow I do quite a bit of coding and use MacTeX for my lab reports.

Should I go with the Macs or buy a Windows laptop?
 
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What "physics software" are you looking at, and what does it say about requirements?
 
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When I upgraded to Apple Silicon awhile back, I didn't have to abandon any software due to compatibility. The current version of MacTeX runs natively on ARM, and I'm pretty sure the previous one did too. The only software I stopped using was DropBox since they still hadn't bothered to release an ARM client at the time and I didn't really use DropBox anymore anyway. The ARM-based systems have been out for a while now, so I would expect most developers who support macOS have already ported their software to Apple Silicon.
 
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@Vanadium 50 I'm still an undergraduate so I've not used a lot of the heavy programs. The ones I use right now are python libraries such at matplot, pandas, astropy and numpy obviously. Our university uses the Anaconda distribution, but my computer can't handle it so I am forced to use Spyder and download some of the libraries myself. Other than python, we have used MATLAB before and I regularly have to use SAOImageDS9.
 
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Dex_ said:
Our university uses the Anaconda distribution, but my computer can't handle it so I am forced to use Spyder and download some of the libraries myself.
You might want to check out compatibility of all of Anaconda on M1 https://www.anaconda.com/blog/new-release-anaconda-distribution-now-supporting-m1
Please note that macOS M1 does not support Qt yet – Anaconda Navigator and Spyder will not be available. Please check back for updates.
Support for other Python things on Apple Silicon (e.g. TensorFlow) is also more complicated.

As an alternative have you looked at what the price of an M1 Mac would get you in (possibly refurbished) desktop hardware with as much screen real estate as you can afford (possibly starting small and upgrading later)? You can still use your laptop for taking notes in class etc, or if it is really dying get a chromebook.

IME expensive laptops suck for coding, writing documents, spreadsheets, just about everything apart from showing off in coffee shops next to a power outlet.
 
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Related to Apple's new ARM CPUs vs, classic x86 for physics?

1. How do Apple's new ARM CPUs compare to classic x86 CPUs for physics applications?

Apple's new ARM CPUs, such as the M1 chip, have shown promising performance for physics applications. While x86 CPUs have traditionally been the standard for scientific computing, ARM CPUs are now catching up in terms of performance and efficiency. The M1 chip, in particular, has demonstrated impressive single-core performance and energy efficiency, making it a viable option for physics simulations and calculations.

2. Are there any limitations to using Apple's ARM CPUs for physics research?

One limitation of using Apple's ARM CPUs for physics research is the lack of compatibility with certain software and tools that are optimized for x86 architecture. However, many developers are working on porting their applications to ARM, and virtualization solutions like Rosetta 2 can help run x86-based software on ARM CPUs. Additionally, the performance gains and energy efficiency of ARM CPUs may outweigh the compatibility issues for some users.

3. Can Apple's ARM CPUs handle complex physics simulations and calculations?

Yes, Apple's ARM CPUs, such as the M1 chip, are capable of handling complex physics simulations and calculations. The M1 chip's high-performance cores and integrated GPU make it well-suited for tasks that require significant computational power, such as running simulations, analyzing data, and performing calculations in physics research. Users have reported impressive performance gains when using ARM CPUs for physics applications.

4. What are the advantages of using Apple's ARM CPUs over classic x86 CPUs for physics work?

Some advantages of using Apple's ARM CPUs for physics work include improved energy efficiency, better single-core performance, and lower heat generation. ARM CPUs are known for their power efficiency, which can be beneficial for running simulations and calculations for extended periods without overheating. Additionally, the M1 chip's unified memory architecture and high-performance cores contribute to faster processing speeds and smoother multitasking.

5. How does the transition to Apple's ARM CPUs affect the physics research community?

The transition to Apple's ARM CPUs has the potential to positively impact the physics research community by offering a new platform for high-performance computing. Researchers can benefit from the energy efficiency, performance gains, and integration of CPU and GPU capabilities in ARM-based systems like the M1 chip. While there may be some initial challenges with software compatibility, the overall shift to ARM architecture could lead to more efficient and powerful computing solutions for physics research.

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