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Notes -
Bit Hyperbolic no ?
I'd say the opposite. GC languages are only unviable for systems that care about exceptional performance.
Quant trading works with GCs. ML & gaming have a unique preference for C++ because of the ecosystem, so I'll treat them as exceptions. Google uses Go for large scale systems (not the core, but pretty much everything else). Clearly it's good enough for most systems work.
I was writing some code to optimise within constraints - basically just a massive pile of nested loops and if statements. It did well so we ported it to production, rewriting everything in C++.
The result was literally hundreds, maybe thousands of times faster. It went from being something that ran with a visible delay to something I could run in real-time.
Fair enough. I work with numeric data. Most loops get vectorized as part of the numeric processing packages I'm using. I can imagine there are situations where nested loops can't be avoided on the critical path, and that causes a lot of pain.
Plus those numeric processing packages will almost certainly be using C or C++ under the hood for speed, because base Python is just far too slow when processing primitives.
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I worked at a startup that was having huge problems with their server responsiveness due to Go's GC. They unfortunately believed the hype that it was a fancy concurrent GC with very small stop-the-world pauses. What they didn't realize was that while the GC was running, many common memory-accessing operations slowed down 10x (due to e.g. memory fences to avoid screwing with the GC). The slow performance would snowball, and you'd end up with the server spending most of its time in an unacceptable high-latency state.
We did manage to get some good performance out of Go eventually, but it was by explicitly writing our code to bypass the GC (including managing our own memory arena). TBH I like Go in general, but I think you underestimate just how costly a GCed language, even with a modern fancy GC, can be.
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Quants care about latency, yes, but they're more than happy to throw a bit more hardware at their problems.
I can see I'll have to be more specific about what I take "performance" to mean. Performance is... efficiency. How much time, how many CPU clock cycles, how much memory, how many watts do you use while performing your task? Latency is one slice of it - a poorly written program will have poor performance on multiple dimensions, including latency - but low-latency alone is not the whole picture. A data center would likely not be happy to know you've reduced their latency at the cost of a large increase in power draw - power and cooling are a major factor in their operations! For game consoles, the hardware is fixed. If you take more compute than the console has to give you to get the next frame ready, your performance is poor. On any platform, if you use more memory than is available, everything suffers as you swap out to disk.
If your overriding concern is latency, to the exclusion of other performance concerns, I guess I can soften to say that GC may be workable.
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