We at Verilog Meetup constructed an exam/interview problem that has an interesting property: if a student tries to figure out a solution by thinking by himself, he usually succeeds; however if he dumps the problem on ChatGPT, the solution fails (does not pass the automated test), and the student goes into a death spiral of futility, kicking ChatGPT to get the solution right.
There is nothing weird about the problem, we do this in the industry all the time:
November 10, 2020 was in many ways a landmark event in the microprocessor industry: Apple unveiled its new Mac Mini, the main feature of which was the new M1 chip, developed in-house. It is not an exaggeration to say that this processor is a landmark achievement for the ARM ecosystem: finally an ARM architecture chip whose performance surpassed x86 architecture chips from competitors such as Intel, a niche that had been dominated for decades.
But the main interest for us is not the M1 processor itself, but the Rosetta 2 binary translation technology. This allows the user to run legacy x86 software that has not been migrated to the ARM architecture. Apple has a lot of experience in developing binary translation solutions and is a recognized leader in this area. The first version of the Rosetta binary translator appeared in 2006 were it aided Apple in the transition from PowerPC to x86 architecture. Although this time platforms were different from those of 2006, it was obvious that all the experience that Apple engineers had accumulated over the years, was not lost, but used to develop the next version - Rosetta 2.
We were keen to compare this new solution from Apple, a similar product Huawei ExaGear (with its lineage from Eltechs ExaGear) developed by our team. At the same time, we evaluated the performance of binary translation from x86 to Arm provided by Microsoft (part of MS Windows 10 for Arm devices) on the Huawei MateBook E laptop. At present, these are the only other x86 to Arm binary translation solution that we are aware of on the open market.
