4 ms·
My understanding is that the performance is based around Apple silicon being optimized for the NeXT/ObjC model of retain/release, which they got down from 30 na
by Eric_WVGG 2y ago
My understanding is that the performance is based around Apple silicon being optimized for the NeXT/ObjC model of retain/release, which they got down from 30 nanoseconds on Intel to 6.5ns on M1 (14ns on emulated Intel).
https://singhkays.com/blog/apple-silicon-m1-black-magic/#is-8-gb-ram-on-x86-intelamd-the-same-as-8-gb-on-apple-silicon-m1 https://singhkays.com/blog/apple-silicon-m1-black-magic/#is-...
IMO 8gb is still barely acceptable for most consumers in 2024, but not for any laptop that you'd expect to get more than say two years of usefulness out of, so… yeah it's about time.
- wmf 2y agoThat increases performance but it doesn't save any RAM.
- Eric_WVGG 2y agoI’m not exactly an expert on this, but I do know from experience that Objective-C programming (and anything coming out of an ARC compiler, like Swift) is a constant game of grabbing memory, using it, and releasing it. My impression is that if you can release memory faster, that means greater availability in the pool. Guesses aside, I spent a lot of time in Xcode on an 8gb M1 while waiting for the M1 Pro to come out three years ago. It was great, much better performing than the 16gb Intel it was replacing. I still don’t think 8gb is really a big deal for most people, getting more is just important for speculative future needs.
- ComputerGuru 2y agoThe behavior you describe would be a function of the memory allocator in use (system allocator, custom allocator) and independent of the hardware. It's at a much, much higher level than the hardware or even the page compression.