On M1 I would expect even better results due to the high memory bandwidth. Step 1: Creating a Mathworks account and activating it. Step 4: Installing X11 (Mac only) These steps are expanded in details below. Step 2: Obtaining the serial number from the UNSW IT website. If I can do it (physicists not natively a programmer) surely the mathworks dev team can! Having implemented now some complex models both in Cuda and on Metal I can say the syntax is very much alike and also a lot of rules of thumb for Cuda hold for Metal also. The basic steps are: Step 1: Obtaining a Mathworks account and activate it. Ever since the M1 release, MATLAB users have been asking the question When is a native Apple Silicon version going to be available. MATLAB beta on Native Apple Silicon available now. That should really not be more then a weeks work for an apple developer developer. MathWorks made use of this and MATLAB has been supported on Apple Silicon Macs via Rosetta 2 since R2020b Update 3. What I would suggest for the Apple silicon implementation team is to just implement the same kind of interface to Metal as exists for Cuda, For users to be able to run their own Metal code in a GPU kernel object and separate gpu variable holders. There are two products which are available on Intel-based Macs but are not compatible with the Rosetta 2 environment: Polyspace and Simulink Desktop Real-Time. Earlier releases of MATLAB may run but are not fully supported. Then just follow the basic procedure to run a metal core. MATLAB R2020b Update 3 and later are supported on Apple silicon Macs through the Rosetta 2 translation environment. In a nutshell: an adjusted make file to include the metal framework to be able to use the mex compile command and in the code simply transfer variable to Metal textures\databuffer and then follow the apple way to run code on this data using an objective C++. For evaluation, I made an interface to Metal on an intel Mac to see if the GPU would help me for a certain algorithm.
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