Again reading C++ Primer 5 Edition. I am on chapter 12 Dynamic memory. Everything is OK. Until this point in the book:
"Because memory is not freed until the last shared_ptr goes away, it can be important to be sure that shared_ptrs don’t stay around after they are no longer needed.The program will execute correctly but may waste memory if you neglect to destroy shared_ptrs that the program does not need.One way that shared_ptrs might stay around after you need them is if you put shared_ptrs in a container and subsequently reorder the container so that you don’t need all the elements.You should be sure to erase shared_ptr elements once you no longer need those elements.
Note
If you put shared_ptrs in a container, and you subsequently need to use some, but not all, of the elements, remember to erase the elements you no longer need."
I don't understand this paragraph can someone explain to me how may shared_ptrs leaks? and an example of the "container" of shared_ptr that can cause leak. Thank you.
It essentially means that as long as you have a std::shared_ptr object in your container the object it points to will not be deleted.
So once you have no more use of that object, you should remove the corresponding std::shared_ptr from your container so the storage can be freed.
If you were to keep adding elements to your container and never removing any, you would essentially leak memory (ofc it will be cleaned up when the reference count hits 0, but until then it's reserved for no reason).
Side note, make sure you always think about when you are using std::shared_ptr. Often a std::unique_ptr is enough and should the need arise to make it shared it's easy to do that.
See Does C++11 unique_ptr and shared_ptr able to convert to each other's type?
also
https://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines#Rr-unique
Related
For example, an immutable CFString can store the length and the character data in the same block of memory. And, more generally, there is NSAllocateObject(), which lets you specify extra bytes to be allocated after the object’s ivars. The amount of storage is determined by the particular instance rather than being fixed by the class. This reduces memory use (one allocation instead of two) and improves locality of reference. Is there a way to do this with Swift?
A rather later reply. 😄 NSAllocateObject() is now deprecated for some reason. However, NSAllocateObject() is really a wrapper around class_createInstance which is not deprecated. So, in principle, one could use this to allocate extra bytes for an object instance.
I can't see why this wouldn't work in Swift. But accessing the extra storage would be messy because you'd have to start fooling around with unsafe pointers and the like. Moreover, if you're not the author of the original class, then you risk conflicting with Apple's ivars, especially in cases where you might be dealing with a class cluster which could potentially have a number of different instance sizes, according to the specific concrete implementation.
I think a safter approach would be to make use of objc_setAssociatedObject and objc_getAssociatedObject, which are accessible in Swift. E.g. Is there a way to set associated objects in Swift?
This page has been quite confusing for me.
It says:
Memory management in newLISP does not rely on a garbage collection algorithm. Memory is not marked or reference-counted. Instead, a decision whether to delete a newly created memory object is made right after the memory object is created.
newLISP follows a one reference only (ORO) rule. Every memory object not referenced by a symbol is obsolete once newLISP reaches a higher evaluation level during expression evaluation. Objects in newLISP (excluding symbols and contexts) are passed by value copy to other user-defined functions. As a result, each newLISP object only requires one reference.
Further down, I see:
All lists, arrays and strings are passed in and out of built-in functions by reference.
I can't make sense of these two.
How can newLISP "not rely on a garbage collection algorithm", and yet pass things by reference?
For example, what would it do in the case of circular references?!
Is it even possible for a LISP to not use garbage collection, without making performance go down the drain? (I assume you could always pass things by value, or you could always perform a full-heap scan whenever you think it might be necessary, but then it seems to me like that would insanely hurt your performance.)
If so, how would it deal with circular references? If not, what do they mean?
Perhaps reading http://www.newlisp.org/ExpressionEvaluation.html helps understanding the http://www.newlisp.org/MemoryManagement.html paper better. Regarding circular references: they do not exist in newLISP, there is no way to create them. The performance question is addressed in a sub chapter of that memory management paper and here: http://www.newlisp.org/benchmarks/
May be working and experimenting with newLISP - i.e. trying to create a circular reference - will clear up most of the questions.
I'm learning about ruby's mark and sweep approach to garbage collecting. I bumped into a few threads here and there (and this article via a SO thread which I can no longer spot), but they seemed to apply to older versions of ruby and a the information in them wasn't always consistent. (As things stand I'm getting the impression that it's mostly reference counting.)
Might anyone with some unrstanding of ruby 1.9.2's internals be around to chime in, on whether ruby knew how to handle the trickier back references and circular references? (Ideally with a few details/good pointers on how it's actually implemented.)
Mark-and-sweep GC, like almost every algorithm commonly labeled as garbage collection save reference counting, handles circular references just fine. This has nothing to do with the specific implementation. Regardless of the actual GC used by Ruby 1.9, it won't have trouble with cycles. Here's a sketch of the approach of mark-and-sweep collectors, but be assured that other collection schemes handle cyclic references just as well.
Mark all things known to be always reachable ("roots", basically everything that's directly in scope - global variables, local variables, etc.)
Mark all not-yet-marked objects referenced by marked objects
Repeat 2 until no references from marked to not-yet-marked objects remain
Enumerate all objects allocated, deallocates those not marked
You see, a circle of references that's reachable "from the outside" doesn't lead to infinite recursion (we don't visit a given object's references more than once) and a circle of references that isn't reachable isn't marked as reachable and thus freed (each element independently) after marking.
I've been creating a temporary object stack- mainly for the use of heap-based STL structures which only actually have temporary lifetimes, but any other temporary dynamically sized allocation too. The one stack performs all types- storing in an unrolled linked list.
I've come a cropper with alignment. I can get the alignment with std::alignment_of<T>, but this isn't really great, because I need the alignment of the next type I want to allocate. Right now, I've just arbitrarily sized each object at a multiple of 16, which as far as I know, is the maximal alignment for any x86 or x64 type. But now, I'm having two pointers of memory overhead per object, as well as the cost of allocating them in my vector, plus the cost of making every size round up to a multiple of 16.
On the plus side, construction and destruction is fast and reliable.
How does this compare to regular operator new/delete? And, what kind of test suites can I run? I'm pretty pleased with my current progress and don't want to find out later that it's bugged in some nasty subtle fashion, so any advice on testing the operations would be nice.
This doesn't really answer your question, but Boost has just recently added a memory pool library in the most recent version.
It may not be exactly what you want, but there is a thorough treatment of alignment which might spark an idea? If the docs are not enough, there is always the source code.
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In a lay-man terminology how does the garbage collection mechanism work?
How an object is identified to be available for garbage collection?
Also, what do Reference Counting, Mark and Sweep, Copying, Train mean in GC algorithms?
When you use a language with garbage collection you wont get access to the memory directly. Rather you are given access to some abstraction on top of that data. One of the things that is properly abstracted away is the the actual location in memory of the data block, as well as pointers to other datablocks. When the garbage collector runs (this happens occasionally) it will check if you still hold a reference to each of the memory blocks it has allocated for you. If you don't it will free that memory.
The main difference between the different types of garbage collectors is their efficiency as well as any limitations on what kind of allocation schemes they can handle.
The simplest is properly reference counting. When ever you create a reference to an object an internal counter on that object is incremented, when you chance the reference or it is no longer in scope, the counter on the (former) target object is decremented. When this counter reaches zero, the object is no longer referred at all and can be freed.
The problem with reference counting garbage collectors is that they cannot deal with circular data. If object A has a reference to object B and that in turn has some (direct or indirect) reference to object A, they can never be freed, even if none of the objects in the chain are refereed outside the chain (and therefore aren't accessible to the program at all).
The Mark and sweep algorithm on the other hand can handle this. The mark and sweep algorithm works by periodically stopping the execution of the program, mark each item the program has allocated as unreachable. The program then runs through all the variables the program has and marks what they point to as reachable. If either of these allocations contain references to other data in the program, that data is then likewise marked as reachable, etc.
This is the mark part of the algorithm. At this point everything the program can access, no matter how indirectly, is marked as reachable and everything the program can't reach is marked as unreachable. The garbage collector can now safely reclaim the memory associated with the objects marked as unreachable.
The problem with the mark and sweep algorithm is that it isn't that efficient -- the entire program has to be stopped to run it, and a lot of the object references aren't going to change.
To improve on this, the mark and sweep algorithm can be extended with so called "generational garbage collection". In this mode objects that have been in the system for some number of garbage collections are promoted to the old generation, which is not checked that often.
This improves efficiency because objects tend to die young (think of a string being changed inside a loop, resulting in perhaps a lifetime of a few hundred cycles) or live very long (the objects used to represent the main window of an application, or the database connection of a servlet).
Much more detailed information can be found on wikipedia.
Added based on comments:
With the mark and sweep algorithm (as well as any other garbage collection algorithm except reference counting) the garbage collection do not run in the context of your program, since it has to be able to access stuff that your program is not capable of accessing directly. Therefore it is not correct to say that the garbage collector runs on the stack.
Reference counting - Each object has
a count which is incremented when
someone takes a reference to the
object, and decremented when someone
releases the reference. When the reference count goes to zero, the object is deleted. COM uses
this approach.
Mark and sweep - Each object has a flag if it is in use. Starting at the root of the object graph (global variables, locals on stacks, etc.) each referenced object gets its flag set, and so on down the chain. At the end, all objects that are not referenced in the graph are deleted.
The garbage collector for the CLR is described in this slidedeck. "Roots" on slide 15 are the sources for the objects that first go into the graph. Their member fields and so on are used to find the other objects in the graph.
Wikipedia describes several of these approaches in much more and better detail.
Garbage collection is simply knowing if there is any future need for variables in your program, and if not, collect and delete them.
Emphasis is on the word Garbage, something that is completely used out in your house is thrown in the trash and the garbage man handles it for you by coming to pick it up and take it away to give you more room in your house trash can.
Reference Counting, Mark and Sweep, Copying, Train etc. are discussed in good detail at GC FAQ
The general way it is done is that the number of references to an object are kept track of in the background, and when that number goes to zero, the object is SUBJECT TO garbage collection, however the GC will not fire up until it is explicitly needed because it is an expensive operation. What happens when it starts is that the GC goes through the managed area of memory and finds every object that has no references left. The gc deletes those objects by first calling their destructors, allowing them to clean up after themselves, then frees the memory. Commonly the GC will then compact the managed memory area by moving every surviving object to one area of memory, allowing more allocations to take place.
Like i said this is one method that i know of, and there is a lot of research being done in this area.
Garbage collection is a big topic, and there are a lot of ways to implement it.
But for the most common in a nutshell, the garbage collector keeps a record of all references to anything created via the new operator, even if that operator's use was hidden from you (for example, in a Type.Create() method). Each time you add a new reference to the object, the root of that reference is determined and added to the list, if needed. A reference is removed whenever it goes out of scope.
When there are no more references to an object, it can (not "will") be collected. To improve performance and make sure necessary cleanup is done correctly, collections are batched for several objects at once and happen over multiple generations.