[gavinray]

@danbolt @billforsternz

Thank you guys for the response, super appreciate it.

I guess, I can understand from an abstract perspective that you can manually tune performance and optimize to a higher degree if you can control memory allocation yourself.

And for a lot of purposes where performance is imperative, like games or embedded devices it can make or break the ability of software to function properly.

But my question then is, if languages like Crystal, Nim, or D (or any other GC lang with similar speed) can operate either at/near the performance of C, why exactly do you need manual memory management?

And if you do need it, I assume many languages that cater to this audience provide some sort of symbolic annotation that allow you to manually control GC where you feel you need it, aye?

[scott00]

I think you are correct in your basic assertion that no one wants manual memory management for its own sake. What they really want is sufficient performance for their use case. The benchmarks you usually see are throughput oriented, and on small heaps. If you have tight latency budgets and/or huge heaps, the performance is not close.

Optional manual memory management sounds great, but I'm skeptical it would work well in practice. The reason is that if the language default is GC, libraries won't be designed for manual memory management, meaning it will be hard for your manual code to interact with data structures created by non-manual parts.

[dotbmp]

"Near C" performance is often not good enough, and usually misleading. You can write poorly performing applications in C, and certain benchmarks may favor or disfavor certain elements of a language. Generally they're created to be "similarly written" in all benchmarked languages, which may seem like the fairest comparison at face value. But what that means is that they are often naively written in one or more of the languages. Expertly written, hand-tailored-to-the-problem-domain C code is almost always going to outperform other languages by a significant margin, especially languages without manual memory management. You can do things in C like use arena allocators to significantly reduce memory performance overhead - things which require low-level control and a non-naive understanding of the problem domain. Garbage collectors can be quite performant, but they aren't capable of this kind of insight. Code that is written in C similarly to a garbage collected language will be similarly naive (another malloc call for each and every allocated thing, versus allocating out of an arena, for instance).

[billforsternz]

As I said, mitigation strategies exist, including manual control of GC etc. It's not true that using GC is universally impossible in embedded / real-time situations. It is true that it can cause performance and non-determinism issues (which are potentially solvable), and it's also true that some developers avoid GC so they don't have to deal with those potential issues. They would prefer to deal with the issues associated with manual memory management.

Who's to say who's right and who's wrong? Ultimately life (and the subset of life that is software development) is a massively complex strategy and tactics game with a myriad of possible playing strategies and no agreed perfect solution.

[Reelin]

> if languages like ... can operate either at/near the performance of C

That depends entirely on how you define and measure performance. If total throughput is your metric, then it's no problem - for example, Go is perfectly acceptable for web services.

Predictability of latency, however, is absolutely _not_ on par with C code. For example, 3D rendering with a GC can easily result in perceptible stuttering if care isn't taken to minimize allocations and manually trigger the GC at appropriate times.

> some sort of symbolic annotation that allow you to manually control GC

It's not that simple. D tried to sell this at one point, but it just doesn't work for large multithreaded programs and things aren't single threaded these days. Manually controlling a global GC means manually balancing, for example, one block of threads that perform lots of allocations and deallocations (and will starve if the GC doesn't run regularly) with soft real time networking code and hard real time VR rendering code. And (for example) you certainly don't want your rendering loop pausing to scan the _entire heap_ (likely multiple gigabytes) on each frame! Alternatively, in the case of Go (and depending on your particular workload) you might not appreciate the concurrent GC constantly trashing the caches.

Custom allocators and non-atomic reference counting are fantastic though.