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Even leaving Rust aside, by choosing a memory-unsafe language, you're saying that the small delta in performance between GC and no-GC is worth more to your app than massive unavoidable-in-practice security problems. Seems extremely dubious.

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Patrick Walton

@pcwalton

May 10

I wonder what fraction of programmers are aware that any GC technique exists other than mark and sweep and naive reference counting.

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the most common complaint about GC i hear isn't the small delta in performance, but the large delta in worst-case latency that makes even soft real-time applications hard to develop

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I thought that fixed in recent years with more latency sensitive algorithms (which some modern languages always use and in case of java you can opt into using)?

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I've never seen them effective in practice. In the real world it seems like with GC you can *maybe* pick one of memory usage, CPU usage, or performance consistency

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Some of this is hard separate out because GC implementations generally come attached to VMs, etc Pretty sure Java's GC outperforms Go's on many metrics but it's hard to tell because of JIT overheads

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OpenJDK design choices are very focused on long running server applications. Design choices for the Android Runtime are far different. Has equally modern concurrent compacting GC with a focus on latency for apps in foreground and memory usage in the background, not throughput.

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Android's JIT compiler is extremely primitive compared to v8 or OpenJDK but that's intentional to preserve battery life and because the focus is on AOT compilation driven by profiles produced by the JIT / interpreter. They distribute those now too:

android-developers.googleblog.com

Improving App Performance with Baseline Profiles

11:25 PM · May 10, 2022Twitter Web App

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Android 5 switched to full AOT compilation for everything other than one-time initialization code because JIT compilation is horrible for memory usage and battery life. Android 6 moved to current hybrid JIT/interpreter/AOT approach where most code used at runtime is AOT compiled.

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Code run with the interpreter / JIT compiler gets recorded in JIT profiles and then that guides AOT compilation. Over time, you end up with AOT compiled code based on how you use apps. Interpreting the one-time init and cold code makes hot code faster and reduces memory usage.

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Yeah, the "Android lag" that you used to see around like Froyo and Gingerbread is totally gone now. A fine example of how work on GC has really helped UX (of course, HW helped things a lot too).

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Android 12 manages to run surprisingly well with 512MB to 1024MB of memory and only efficiency cores in the Android Go configuration. It's far smoother than Android 4 was on a flagship SoC with 2GB of memory. It has actually gotten genuinely leaner and faster over time.

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