GC as it is promoted today is a giant step that gives programmers one benefit, solving one problem, while introducing a immeasurable pile of complexity to the system creating another pile of problems that are still not fixed today. And to fix some of these problems (like speed) you have to introduce more complexity.
There are plenty of contexts where speed is a non-issue. In those cases, GC has been a huge win. The conceptual simplicity is the important part. The cost of the resources that would be saved with explicit and optimized memory management would be far outweighed by the resources required to implement such things.
The original idea is simple, but nobody uses the original idea because it performs so badly.
This is simply not true.
In the context of IO-bound enterprise systems, I've seen generational GC perform admirably, almost magically. As a lark, I've put infinite loops into such apps that do nothing but allocate new objects, and unless you are doing an exceptionally intense operation, you couldn't tell the difference. Properly tuned generational GC can be a truly fantastic seeming thing!
However, I will agree that the concerns Linus highlights are real, and that refcounting systems, like the one in iOS are by far better choices in many contexts.
EDIT: The above system I victimized, I only victimized in the TEST environment, but it was populated with something like 2-week old production data. The application in question is a traditional client/server desktop app used by a major energy company and had 800 active users at the time, handling millions in transactions every minute.
IDEA: If someone had an augmented ref-counting system with a runtime containing an optional cycle-detector and something like LINT but for the runtime reference graph, one would get most of the benefits of GC with the efficiency of the ref-counting system. I half expect someone to tell me that this already exists for Python.
In 2004 Bacon et al. showed that tracing GC and ref-counting GC are special cases of a more general framework, and that it is possible to combine them to get the benefits of both. See "A Unified Theory of Garbage Collection" here:
> I've seen generational GC perform admirably, almost magically. As a lark, I've put infinite loops into such apps that do nothing but allocate new objects
While I agree that generational GC can perform spectacularly well, what you're describing is close to the case it's optimized for, not close to its worst case. The worst case is that you allocate lots and lots of small objects and then write a pointer to all of them into a tenured garbage object.
> I half expect someone to tell me that this already exists for Python.
Yes, that's how Python works, except that I don't know what you mean by "something like LINT but for the runtime reference graph."
While I agree that generational GC can perform spectacularly well, what you're describing is close to the case it's optimized for, not close to its worst case
Here's the thing: Most of the rest of the app was rather close to the case it's optimized for.
I don't know what you mean by "something like LINT but for the runtime reference graph."
Something that tells you that you've created a reference graph with a cycle, you have a memory leak, or that you're using references in some other stupid or suboptimal way. I'm not even sure if there's a way to automatically detect anything like the last category, though the first two are certainly detectable. Basically, you take most of the infrastructure of GC, and you just turn it into a runtime advisor to warn devs and testers of mistakes.
Great Circle commercialized the Boehm collector back in the 1990s, and I seem to recall that most of their customers were using it to tell them when they had a memory leak or reused freed memory, not to remove the need for reference counting altogether. But it didn't tell you about cyclic references, unless they resulted in a memory leak.
> IDEA: If someone had an augmented ref-counting system with a runtime containing an optional cycle-detector and something like LINT but for the runtime reference graph, one would get most of the benefits of GC with the efficiency of the ref-counting system. I half expect someone to tell me that this already exists for Python.
Or you could do what Rust <https://github.com/graydon/rust/wiki/Language-FAQ>; does, and have different types of objects; stateful and stateless. Stateless object cannot have cycles (since you can't construct them in stateless objects, unless you're in a lazy language), and so reference counting can be used for stateless objects. Stateful objects, which can have cycles, are managed by the garbage collector.
Rust sounds like a really interesting idea, and I'd love to give it a try, but sadly it's still in the "some assembly required" stage as they work on bootstrapping it so the only real projects that are worthwhile to do with it yet are helping out with the bootstrapping process.
In a way, I do as well.
GC as it is promoted today is a giant step that gives programmers one benefit, solving one problem, while introducing a immeasurable pile of complexity to the system creating another pile of problems that are still not fixed today. And to fix some of these problems (like speed) you have to introduce more complexity.
There are plenty of contexts where speed is a non-issue. In those cases, GC has been a huge win. The conceptual simplicity is the important part. The cost of the resources that would be saved with explicit and optimized memory management would be far outweighed by the resources required to implement such things.
The original idea is simple, but nobody uses the original idea because it performs so badly.
This is simply not true.
In the context of IO-bound enterprise systems, I've seen generational GC perform admirably, almost magically. As a lark, I've put infinite loops into such apps that do nothing but allocate new objects, and unless you are doing an exceptionally intense operation, you couldn't tell the difference. Properly tuned generational GC can be a truly fantastic seeming thing!
However, I will agree that the concerns Linus highlights are real, and that refcounting systems, like the one in iOS are by far better choices in many contexts.
EDIT: The above system I victimized, I only victimized in the TEST environment, but it was populated with something like 2-week old production data. The application in question is a traditional client/server desktop app used by a major energy company and had 800 active users at the time, handling millions in transactions every minute.
IDEA: If someone had an augmented ref-counting system with a runtime containing an optional cycle-detector and something like LINT but for the runtime reference graph, one would get most of the benefits of GC with the efficiency of the ref-counting system. I half expect someone to tell me that this already exists for Python.