In Lua, how to determine the size of an object? - memory

Is there a way, in Lua, to determine the (in memory) size of an object?
I found an article on Gamepedia about Lua object memory sizes, but it is not general and precise.

I would give the same explanation as #NicolBolas, but different answers to the questions.
Is there a way, in Lua, to determine the (in memory)size of an object?
Yes, but you may need to use an external module for that. See my earlier answer and specifically lua-getsize module.
Is there a way, in Lua, to determine if the table to be stored is greater than the MP size?
If you know the size of the table with X elements, you can probably extrapolate to a table with Y elements of approximately the same content, but you wont be able to limit the allocations to a particular size unless you use your own allocator that has that logic.

Is there a way, in Lua, to determine if the table to be stored is greater than the MP size?
No.
Is there a way, in Lua, to determine the (in memory)size of an object?
No.
Lua is not responsible for things like capping memory and so forth. That ought to be handled from the C code that creates and manages the Lua state. So if you have a 16MB limit, then that needs to be built into the lua_State when you call lua_newstate. You pass it an allocation function that needs to keep track of all such allocations. It would also allocate storage from the memory pool, not from the heap.
Of course, the allocator can't tell exactly why an allocation is happening. So there's no way to limit just this one specific table to 16MB, if you intend for the Lua state to also do other things.
If you have such specific memory needs for just this one table, you probably need to allocate and store it in C/C++, and then use the Lua interface to expose it to Lua to read/manipulate.

Related

Better to allocate too much memory on the stack, or the correct amount on the heap?

I have just started learning rust, and it is my first proper look into a low level language (I do python, usually). Part of the tutorial explains that a string literal is stored on the stack, because it has a fixed (and known) size; it also explains that a non-initialised string is stored on the heap, so that its size can grow as necessary.
My understanding is that the stack is much faster than the heap. In the case of a string whose size is unknown, but I know it will not ever require more than n bytes, does it make sense to allocate space on the stack for the maximum size, instead of sticking it on the heap?
The purpose of this question is not to solve a problem, but to help me understand, so I would appreciate verbose and detailed answers!
The difference in performance between the stack and the heap comes due to the fact that objects in the heap may change size at run time, and they must then be reallocated somewhere else in the heap.
Now for the verbose part. Imagine you have an integer i32. This number will always be the same size, so any modifications made to it will occur in place. When it goes out of scope (it stops being needed in the program) it will either be deleted, or, a more efficient solution, it will be deleted along with the whole stack it belongs to.
Now you want to create a String. So you create it in the heap and give it a value. And then you modify it and add some characters to it. Now two things can happen.
There is free memory after the string, so the allocator uses this memory to write the new part.
There already is an object allocated in the memory right after the string, and of course, you don't want to overwrite it. So the allocator looks for the next free memory space with enough size to hold the new string and copies into it that string. Then deletes the old one, freeing that memory.
As you can see in the heap the number of operations to be made is incredibly higher than in the stack, so its performance will be lower.
Now, in your case, there are some methods specifically for memory reservation. String::reserve() and String::reserve_exact(). I would recommend you to look at the documentation for Rust always. Usually there already is a std method for what you want.

Does the order or syntax of allocate statement affect performance? (Fortran)

Because of having performance issues when passing a code from static to dynamic allocation, I started to wander about how memory allocation is managed in a Fortran code.
Specifically, in this question, I wander if the order or syntax used for the allocate statement makes any difference. That is, does it make any difference to allocate vectors like:
allocate(x(DIM),y(DIM))
versus
allocate(x(DIM))
allocate(y(DIM))
The syntax suggests that in the first case the program would allocate all the space for the vectors at once, possibly improving the performance, while in the second case it must allocate the space for one vector at a time, in such a way that they could end up far from each other. If not, that is, if the syntax does not make any difference, I wander if there is a way to control that allocation (for instance, allocating a vector for all space and using pointers to address the space allocated as multiple variables).
Finally, I notice now that I don't even know one thing: an allocate statement guarantees that at least a single vector occupies a contiguous space in memory (or the best it can?).
From the language standard point of view both ways how to write them are possible. The compiler is free to allocate the arrays where it wants. It normally calls malloc() to allocate some piece of memory and makes the allocatable arrays from that piece.
Whether it might allocate a single piece of memory for two different arrays in a single allocate statement is up to the compiler, but I haven't heard about any compiler doing that.
I just verified that my gfortran just calls __builtin_malloc two times in this case.
Another issue is already pointed out by High Performance Mark. Even when malloc() successfully returns, the actual memory pages might still not be assigned. On Linux that happens when you first access the array.
I don't think it is too important if those arrays are close to each other in memory or not anyway. The CPU can cache arrays from different regions of address space if it needs them.
Is there a way how to control the allocation? Yes, you can overload the malloc by your own allocator which does some clever things. It may be used to have always memory aligned to 32-bytes or similar purposes (example). Whether you will improve performance of your code by allocating things somehow close to each other is questionable, but you can have a try. (Of course this is completely compiler-dependent thing, a compiler doesn't have to use malloc() at all, but mostly they do.) Unfortunately, this will only works when the calls to malloc are not inlined.
There are (at least) two issues here, firstly the time taken to allocate the memory and secondly the locality of memory in the arrays and the impact of this on performance. I don't know much about the actual allocation process, although the links suggested by High Performance Mark and the answer by Vadimir F cover this.
From your question, it seems you are more interested in cache hits and memory locality given by arrays being next to each other. I would guess there is no guarantee either allocate statement ensures both arrays next to each other in memory. This is based on allocating arrays in a type, which in the fortran 2003 MAY 2004 WORKING DRAFT J3/04-007 standard
NOTE 4.20
Unless the structure includes a SEQUENCE statement, the use of this terminology in no way implies that these components are stored in this, or any other, order. Nor is there any requirement that contiguous storage be used.
From the discussion with Vadimir F, if you put allocatable arrays in a type and use the sequence keyword, e.g.
type botharrays
SEQUENCE
double precision, dimension(:), allocatable :: x, y
end type
this DOES NOT ensure they are allocated as adjacent in memory. For static arrays or lots of variables, a sequential type sounds like it may work like your idea of "allocating a vector for all space and using pointers to address the space allocated as multiple variables". I think common blocks (Fortran 77) allowed you to specify the relationship between memory location of arrays and variables in memory, but don't work with allocatable arrays either.
In short, I think this means you cannot ensure two allocated arrays are adjacent in memory. Even if you could, I don't see how this will result in a reduction in cache misses or improved performance. Even if you typically use the two together, unless the arrays are small enough that the cache will include multiple arrays in one read (assuming reads are allowed to go beyond array bounds) you won't benefit from the memory locality.

How to get "sizeof" a table in Lua?

I'm dabbling in Love2D using Lua and have just implemented a StateMachine to handle transitions between a set of states e.g. IntroState, MenuState, PlayState etc..
In previous programs I usally release objects and/or states that are only a "one-time-deal", iow will only be presented to the player once during the lifetime of the application. In C++ I use the sizeof operator which returns the size in bytes of the passed object, just to get some feedback of how much memory I release at a certain point.
Are there any corresponding keyword or trick in Lua to achieve this?
If you need fine-grained information, you can use getsize as #siffiejoe mentioned in combination with some table traversal to get to all local and global objects. If you need more coarse-grained approach, you can use collectgarbage('count') to get the total memory used by Lua.
This SO answer and this lua discussion on memory tracking may be of some help. Note that you don't have control over memory release as it's handled by the garbage collector (although there are several GC settings you can tweak).

boost lockfree spsc_queue cache memory access

I need to be extremely concerned with speed/latency in my current multi-threaded project.
Cache access is something I'm trying to understand better. And I'm not clear on how lock-free queues (such as the boost::lockfree::spsc_queue) access/use memory on a cache level.
I've seen queues used where the pointer of a large object that needs to be operated on by the consumer core is pushed into the queue.
If the consumer core pops an element from the queue, I presume that means the element (a pointer in this case) is already loaded into the consumer core's L2 and L1 cache. But to access the element, does it not need to access the pointer itself by finding and loading the element either from either the L3 cache or across the interconnect (if the other thread is on a different cpu socket)? If so, would it maybe be better to simply send a copy of the object that could be disposed of by the consumer?
Thank you.
C++ principally a pay-for-what-you-need eco-system.
Any regular queue will let you choose the storage semantics (by value or by reference).
However, this time you ordered something special: you ordered a lock free queue.
In order to be lock free, it must be able to perform all the observable modifying operations as atomic operations. This naturally restricts the types that can be used in these operations directly.
You might doubt whether it's even possible to have a value-type that exceeds the system's native register size (say, int64_t).
Good question.
Enter Ringbuffers
Indeed, any node based container would just require pointer swaps for all modifying operations, which is trivially made atomic on all modern architectures.
But does anything that involves copying multiple distinct memory areas, in non-atomic sequence, really pose an unsolvable problem?
No. Imagine a flat array of POD data items. Now, if you treat the array as a circular buffer, one would just have to maintain the index of the buffer front and end positions atomically. The container could, at leisure update in internal 'dirty front index' while it copies ahead of the external front. (The copy can use relaxed memory ordering). Only as soon as the whole copy is known to have completed, the external front index is updated. This update needs to be in acq_rel/cst memory order[1].
As long as the container is able to guard the invariant that the front never fully wraps around and reaches back, this is a sweet deal. I think this idea was popularized in the Disruptor Library (of LMAX fame). You get mechanical resonance from
linear memory access patterns while reading/writing
even better if you can make the record size aligned with (a multiple) physical cache lines
all the data is local unless the POD contains raw references outside that record
How Does Boost's spsc_queue Actually Do This?
Yes, spqc_queue stores the raw element values in a contiguous aligned block of memory: (e.g. from compile_time_sized_ringbuffer which underlies spsc_queue with statically supplied maximum capacity:)
typedef typename boost::aligned_storage<max_size * sizeof(T),
boost::alignment_of<T>::value
>::type storage_type;
storage_type storage_;
T * data()
{
return static_cast<T*>(storage_.address());
}
(The element type T need not even be POD, but it needs to be both default-constructible and copyable).
Yes, the read and write pointers are atomic integral values. Note that the boost devs have taken care to apply enough padding to avoid False Sharing on the cache line for the reading/writing indices: (from ringbuffer_base):
static const int padding_size = BOOST_LOCKFREE_CACHELINE_BYTES - sizeof(size_t);
atomic<size_t> write_index_;
char padding1[padding_size]; /* force read_index and write_index to different cache lines */
atomic<size_t> read_index_;
In fact, as you can see, there are only the "internal" index on either read or write side. This is possible because there's only one writing thread and also only one reading thread, which means that there could only be more space at the end of write operation than anticipated.
Several other optimizations are present:
branch prediction hints for platforms that support it (unlikely())
it's possible to push/pop a range of elements at once. This should improve throughput in case you need to siphon from one buffer/ringbuffer into another, especially if the raw element size is not equal to (a whole multiple of) a cacheline
use of std::unitialized_copy where possible
The calling of trivial constructors/destructors will be optimized out at instantiation time
the unitialized_copy will be optimized into memcpy on all major standard library implementations (meaning that e.g. SSE instructions will be employed if your architecture supports it)
All in all, we see a best-in-class possible idea for a ringbuffer
What To Use
Boost has given you all the options. You can elect to make your element type a pointer to your message type. However, as you already raised in your question, this level of indirection reduces locality of reference and might not be optimal.
On the other hand, storing the complete message type in the element type could become expensive if copying is expensive. At the very least try to make the element type fit nicely into a cache line (typically 64 bytes on Intel).
So in practice you might consider storing frequently used data right there in the value, and referencing the less-of-used data using a pointer (the cost of the pointer will be low unless it's traversed).
If you need that "attachment" model, consider using a custom allocator for the referred-to data so you can achieve memory access patterns there too.
Let your profiler guide you.
[1] I suppose say for spsc acq_rel should work, but I'm a bit rusty on the details. As a rule, I make it a point not to write lock-free code myself. I recommend anyone else to follow my example :)

What is the purpose of each of the memory locations, stack, heap, etc? (lost in technicalities)

Ok, I asked the difference between Stackoverflow and bufferoverflow yesterday and almost getting voted down to oblivion and no new information.
So it got me thinking and I decided to rephrase my question in the hopes that I get reply which actually solves my issue.
So here goes nothing.
I am aware of four memory segments(correct me if I am wrong). The code, data, stack and heap. Now AFAIK the the code segment stores the code, while the data segment stores the data related to the program. What seriously confuses me is the purpose of the stack and the heap!
From what I have understood, when you run a function, all the related data to the function gets stored in the stack and when you recursively call a function inside a function, inside of a function... While the function is waiting on the output of the previous function, the function and its necessary data don't pop out of the stack. So you end up with a stack overflow. (Again please correct me if I am wrong)
Also I know what the heap is for. As I have read someplace, its for dynamically allocating data when a program is executing. But this raises more questions that solves my problems. What happens when I initially initialize my variables in the code.. Are they in the code segment or in the data segment or in the heap? Where do arrays get stored? Is it that after my code executes all that was in my heap gets erased? All in all, please tell me about heap in a more simplified manner than just, its for malloc and alloc because I am not sure I completely understand what those terms are!
I hope people when answering don't get lost in the technicalities and can keep the terms simple for a layman to understand (even if the concept to be described is't laymanish) and keep educating us with the technical terms as we go along. I also hope this is not too big a question, because I seriously think they could not be asked separately!
What is the stack for?
Every program is made up of functions / subroutines / whatever your language of choice calls them. Almost always, those functions have some local state. Even in a simple for loop, you need somewhere to keep track of the loop counter, right? That has to be stored in memory somewhere.
The thing about functions is that the other thing they almost always do is call other functions. Those other functions have their own local state - their local variables. You don't want your local variables to interfere with the locals in your caller. The other thing that has to happen is, when FunctionA calls FunctionB and then has to do something else, you want the local variables in FunctionA to still be there, and have their same values, when FunctionB is done.
Keeping track of these local variables is what the stack is for. Each function call is done by setting up what's called a stack frame. The stack frame typically includes the return address of the caller (for when the function is finished), the values for any method parameters, and storage for any local variables.
When a second function is called, then a new stack frame is created, pushed onto the top of the stack, and the call happens. The new function can happily work away on its stack frame. When that second function returns, its stack frame is popped (removed from the stack) and the caller's frame is back in place just like it was before.
So that's the stack. So what's the heap? It's got a similar use - a place to store data. However, there's often a need for data that lives longer than a single stack frame. It can't go on the stack, because when the function call returns, it's stack frame is cleaned up and boom - there goes your data. So you put it on the heap instead. The heap is a basically unstructured chunk of memory. You ask for x number of bytes, and you get it, and can then party on it. In C / C++, heap memory stays allocated until you explicitly deallocate. In garbage collected languages (Java/C#/Python/etc.) heap memory will be freed when the objects on it aren't used anymore.
To tackle your specific questions from above:
What's the different between a stack overflow and a buffer overflow?
They're both cases of running over a memory limit. A stack overflow is specific to the stack; you've written your code (recursion is a common, but not the only, cause) so that it has too many nested function calls, or you're storing a lot of large stuff on the stack, and it runs out of room. Most OS's put a limit on the maximum size the stack can reach, and when you hit that limit you get the stack overflow. Modern hardware can detect stack overflows and it's usually doom for your process.
A buffer overflow is a little different. So first question - what's a buffer? Well, it's a bounded chunk of memory. That memory could be on the heap, or it could be on the stack. But the important thing is you have X bytes that you know you have access to. You then write some code that writes X + more bytes into that space. The compiler has probably already used the space beyond your buffer for other things, and by writing too much, you've overwritten those other things. Buffer overruns are often not seen immediately, as you don't notice them until you try to do something with the other memory that's been trashed.
Also, remember how I mentioned that return addresses are stored on the stack too? This is the source of many security issues due to buffer overruns. You have code that uses a buffer on the stack and has an overflow vulnerability. A clever hacker can structure the data that overflows the buffer to overwrite that return address, to point to code in the buffer itself, and that's how they get code to execute. It's nasty.
What happens when I initially initialize my variables in the code.. Are they in the code segment or in the data segment or in the heap?
I'm going to talk from a C / C++ perspective here. Assuming you've got a variable declaration:
int i;
That reserves (typically) four bytes on the stack. If instead you have:
char *buffer = malloc(100);
That actually reserves two chunks of memory. The call to malloc allocates 100 bytes on the heap. But you also need storage for the pointer, buffer. That storage is, again, on the stack, and on a 32-bit machine will be 4 bytes (64-bit machine will use 8 bytes).
Where do arrays get stored...???
It depends on how you declare them. If you do a simple array:
char str[128];
for example, that'll reserve 128 bytes on the stack. C never hits the heap unless you explicitly ask it to by calling an allocation method like malloc.
If instead you declare a pointer (like buffer above) the storage for the pointer is on the stack, the actual data for the array is on the heap.
Is it that after my code executes all that was in my heap gets erased...???
Basically, yes. The OS will clean up the memory used by a process after it exits. The heap is a chunk of memory in your process, so the OS will clean it up. Although it depends on what you mean by "clean it up." The OS marks those chunks of RAM as now free, and will reuse it later. If you had explicit cleanup code (like C++ destructors) you'll need to make sure those get called, the OS won't call them for you.
All in all, please tell me about heap in a more simplified manner than just, its for malloc and alloc?
The heap is, much like it's name, a bunch of free bytes that you can grab a piece at a time, do whatever you want with, then throw back to use for something else. You grab a chunk of bytes by calling malloc, and you throw it back by calling free.
Why would you do this? Well, there's a couple of common reasons:
You don't know how many of a thing
you need until run time (based on
user input, for example). So you
dynamically allocate on the heap as
you need them.
You need large data structures. On
Windows, for example, a thread's
stack is limited by default to 1
meg. If you're working with large
bitmaps, for example, that'll be a
fast way to blow your stack and get
a stack overflow. So you grab that
space of the heap, which is usually
much, much larger than the stack.
The code, data, stack and heap?
Not really a question, but I wanted to clarify. The "code" segment contains the executable bytes for your application. Typically code segments are read only in memory to help prevent tampering. The data segment contains constants that are compiled into the code - things like strings in your code or array initializers need to be stored somewhere, the data segment is where they go. Again, the data segment is typically read only.
The stack is a writable section of memory, and usually has a limited size. The OS will initialize the stack and the C startup code calls your main() function for you. The heap is also a writable section of memory. It's reserved by the OS, and functions like malloc and free manage getting chunks out of it and putting them back.
So, that's the overview. I hope this helps.
With respect to stack... This is precicely where the parameters and local variables of the functions / procedures are stored. To be more precise, the params and local variables of the currently executing function is only accessible from the stack... Other variables that belong to chain of functions that were executed before it will be in stack but will not be accessible until the current function completed its operations.
With respect global variables, I believe these are stored in data segment and is always accessible from any function within the created program.
With respect to Heap... These are additional memories that can be made allotted to your program whenever you need them (malloc or new)... You need to know where the allocated memory is in heap (address / pointer) so that you can access it when you need. Incase you loose the address, the memory becomes in-accessible, but the data still remains there. Depending on the platform and language this has to be either manually freed by your program (or a memory leak occurs) or needs to be garbage collected. Heap is comparitively huge to stack and hence can be used to store large volumes of data (like files, streams etc)... Thats why Objects / Files are created in Heap and a pointer to the object / file is stored in stack.
In terms of C/C++ programs, the data segment stores static (global) variables, the stack stores local variables, and the heap stores dynamically allocated variables (anything you malloc or new to get a pointer to). The code segment only stores the machine code (the part of your program that gets executed by the CPU).

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