Review of Apple Silicon macOS for brain imaging research
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This repository reviews the challenges and potential of ARM-based Apple Silicon macOS for brain imaging research. It aims to inform scientists and researchers about the compatibility, performance, and limitations of this new hardware architecture for their specific workflows, highlighting potential future benefits if key software and hardware limitations are addressed.
How It Works
The project evaluates Apple Silicon's suitability for neuroimaging by benchmarking popular tools like AFNI, dcm2niix, FSL, and SPM. It compares performance against Intel and AMD CPUs, focusing on factors like CPU core utilization, memory bandwidth, and the impact of architectural differences (e.g., unified memory, Metal vs. CUDA). The analysis also details software compatibility issues, compiler support, and the implications of macOS security features for scientific software distribution.
Quick Start & Requirements
Highlighted Details
Maintenance & Community
This is a review document, not an active software project. The content is maintained by the author(s) of the README, with updates reflecting new hardware releases (M1 Pro/Max, M2) and software developments. No community channels or active development are indicated.
Licensing & Compatibility
The content of this repository is a review and analysis. No software is provided for installation or execution. Licensing information is not applicable.
Limitations & Caveats
The document explicitly states that many specific details regarding tool support are dated due to the rapid pace of software porting. It strongly discourages scientists from purchasing Apple Silicon for productive work in the short term unless they are developers willing to tackle porting challenges.
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