std::vector increasing peak memory - c++

This is in continuation of my last question. I am failed to understand the memory taken up by vector. Problem skeleton:
Consider an vector which is an collection of lists and lists is an collection of pointers. Exactly like:
std::vector<std::list<ABC*> > vec;
where ABC is my class. We work on 64bit machines, so size of pointer is 8 bytes.
At the start of my flow in the project, I resize this vector to an number so that I can store lists at respective indexes.
vec.resize(613284686);
At this point, capacity and size of the vector would be 613284686. Right. After resizing, I am inserting the lists at corresponding indexes as:
// Some where down in the program, make these lists. Simple push for now.
std::list<ABC*> l1;
l1.push_back(<pointer_to_class_ABC>);
l1.push_back(<pointer_to_class_ABC>);
// Copy the list at location
setInfo(613284686, l1);
void setInfo(uint64_t index, std::list<ABC*> list>) {
std::copy(list.begin(), list.end(), std::back_inserter(vec.at(index));
}
Alright. So inserting is done. Notable things are:
Size of vector is : 613284686
Entries in the vector is : 3638243731 // Calculated this by going over vector indexes and add the size of std::lists at each index.
Now, since there are 3638243731 entries of pointers, I would expect memory taken by this vector is ~30Gb. 3638243731 * 8(bytes) = ~30Gb.
BUT BUT When I have this data in memory, memory peaks to, 400G.
And then I clear up this vector with:
std::vector<std::list<nl_net> >& ccInfo = getVec(); // getVec defined somewhere and return me original vec.
std::vector<std::list<nl_net> >::iterator it = ccInfo.begin();
for(; it != ccInfo.end(); ++it) {
(*it).clear();
}
ccInfo.clear(); // Since it is an reference
std::vector<std::list<nl_net> >().swap(ccInfo); // This makes the capacity of the vector 0.
Well, after clearing up this vector, memory drops down to 100G. That is too much holding from an vector.
Would you all like to correct me what I am failing to understand here?
P.S. I can not reproduce it on smaller cases and it is coming in my project.

vec.resize(613284686);
At this point, capacity and size of the vector would be 613284686
It would be at least 613284686. It could be more.
std::vector<std::list<nl_net> >().swap(ccInfo); // This makes the capacity of the vector 0.
Technically, there is no guarantee by the standard that a default constructed vector wouldn't have capacity other than 0... But in practice, this is probably true.
Now, since there are 3638243731 entries of pointers, I would expect memory taken by this vector is ~30Gb. 3638243731 * 8(bytes)
But the vector doesn't contain pointers. It contains std::list<ABC*> objects. So, you should expect vec.capacity() * sizeof(std::list<ABC*>) bytes used by the buffer of the vector itself. Each list has at least a pointer to beginning and the end.
Furthermore, you should expect each element in each of the lists to use memory as well. Since the list is doubly linked, you should expect about two pointers plus the data (a third pointer) worth of memory for each element.
Also, each pointer in the lists apparently points to an ABC object, and each of those use sizeof(ABC) memory as well.
Furthermore, since each element of the linked lists are allocated separately, and each dynamic allocation requires book-keeping so that they can be individually de-allocated, and each allocation must be aligned to the maximum native alignment, and the free store may have fragmented during the execution, there will be much overhead associated with each dynamic allocation.
Well, after clearing up this vector, memory drops down to 100G.
It is quite typical for the language implementation to retain (some) memory it has allocated from the OS. If your target system documents an implementation specific function for explicitly requesting release of such memory, then you could attempt using that.
However, if the vector buffer wasn't the latest dynamic allocation, then its deallocation may have left a massive reusable area in the free store, but if there exists later allocations, then all that memory might not be releasable back to the OS.
Even if the langauge implementation has released the memory to the OS, it is quite typical for the OS to keep the memory mapped for the process until another process actually needs the memory for something else. So, depending on how you're measuring memory use, the results might not necessarily be meaningful.
General rules of thumb that may be useful:
Don't use a vector unless you use all (or most) of the indices. In case where you don't, consider a sparse array instead (there is no standard container for such data structure though).
When using vector, reserve before resize if you know the upper bound of allocation.
Don't use linked lists without a good reason.
Don't rely on getting all memory back from peak usage (back to the OS that is; The memory is still usable for further dynamic allocations).
Don't stress about virtual memory usage.

std::list is a fragmented memory container. Typically each node MUST have the data it is storing, plus the 2 prev/next pointers, and then you have to add in the space required within the OS allocation table (typically 16 or 32 bytes per allocation - depending on OS). You then have to account for the fact all allocations must be returned on a 16byte boundary (on Intel/AMD based 64bit machines anyway).
So using the example of std::list<ABC*> the size of a pointer is 8, however you will need at least 48bytes to store each element (at least).
So memory usage for ONLY the list entries is going to be around: 3638243731 * 48(bytes) = ~162Gb.
This is of course assuming that there is no memory fragmentation (where there may be a block of 62bytes free, and the OS returns the entire block of 62 rather than the 48 requested). We are also assuming here that the OS has a minimum allocation size of 48 bytes (and not say, 64bytes, which would not be overly silly, but would push the usage up far higher).
The size of the std::lists themselves within the vector comes to around 18GB. So in total we are looking at 180Gb at least to store that vector. It would not be beyond the realm of possibility that the extra allocations are additional OS book keeping info, for all of those individual memory allocations (e.g. lists of loaded memory pages, lists of swapped out memory pages, the read/write/mmap permissions, etc, etc).
As a final note, instead of using swap on a newly constructed vector, you can just use shrink to fit.
ccInfo.clear();
ccInfo.shrinkToFit();

The main vector needs some more consideration. I get the impression it will always be a fixed size. So why not use a std::array instead? A std::vector always allocates more memory than it needs to allow for growth. The bigger your vector the bigger the reservation of memory to allow for more even growth. The reasononing behind is to keep relocations in memory to a minimum. Relocations on really big vectors take up huge amounts of time so a lot of extra memory is reserved to prevent this.
No vector function that can delete elements (such as vector::clear and ::erase) also deallocates memory (e.g. lower the capacity). The size will decrease but the capacity doesn't. Again, this is meant to prevent relocations; if you delete you are also very likely to add again. ::shrink_to_fit also doesn't guarantuee you that all of the used memory is released.*
Next is the choice of a list to store elements. Is a list really applicable? Lists are strong in random access/insertion/removal operations. Are you really constantly adding and removing ABC objects to the list in random locations? Or is another container type with different properties but with contiguous memory more suitable? Another std::vector or std::array perhaps. If the answer is yes than you're pretty much stuck with a list and its scattered memory allocations. If no, than you could win back a lot of memory by using a different container type.
So, what is it you really want to do? Do you really need dynamic growth on both the main container and its elements? Do you really need random manipulation? Or can you use fixed-size arrays for both container and ABC objects and use iteration instead? When contemplating this you might want to read up on the available containers and their properties on en.cppreference.com. It will help you decide what is most appropriate.
*For the fun of it I dug around in VS2017's implementation and it creates an entirely new vector without the growth segment, copies the old elements and then reassigns the internal pointers of the old vector to the new one while deleting the old memory. So at least with that compiler you can count on memory being released.

Related

How does STL containers keep track of the current size of container over the total size?

Given
vector<int> a;
If a.push_back() is done, how does the vector knows whether to increase the size by reallocating memory or there is space available (Because vector allocates some extra space when size is full to reduce overhead).
P.S. Does same technique applies for other types of containers like stack, queue etc.
I think that it does the same thing as "struct" in C.
The method capacity() returns the number of items that can be stored in the vector without a reallocation.
The method size() returns the number of items which are currently stored in the vector.
Prior to inserting another item, it stands to reason that if size() == capacity() then more capacity will need to be made available. This will involve a reallocation to make more capacity available.
Does same technique applies for other types of containers like stack, queue etc.
stack and queue are built on top of other std containers. These underlying containers (normally vector or deque) employ a similar technique.
I think that it does the same thing as "struct" in C.
No.
In general, a vector ( and incidently a List in C# ), will allocate a block of memory. As you add elements to it, it will mark more and more of that memory as consumed. Then, when the block is full, it will allocate a new larger block, copy the contents into the new larger block, and delete the old one. Again the new larger block has more free space, and then, again, it can be filled up. The idea is that vector always has a contiguous space so it can be used in applications where one would consider an array. Because it has contiguous space, machine instructions for accessing a single element are trivial and so random access is very fast. List in C# has similar semantics. The implementation dependent thing has a lot to do with how much bigger that new bigger block is. Sometimes they make it a percentage bigger. Sometimes they just double the size.

Which C++ stl container should I use?

Imagine the following requirements:
measurement data should be logged and the user should be able to iterate through the data.
uint32_t timestamp;
uint16_t place;
struct SomeData someData;
have a timestamp (uint32_t), a place (uint16_t) and some data in a struct
have a constant number of datasets. If a new one arrives, the oldest is thrown away.
the number of "place" is dynamic, the user can insert new ones during runtime
it should be possible to iterate through the data to the next newer or older dataset but only if the place is the same
need to insert at the end only
memory should be allocated once at program start
insertion need not to be fast but should not block other threads for a long time which might be iterating through the container
memory requirement should be low
EDIT: - The container should all the memory which is not used otherwise, therefore it can be large.
I am not sure which container I should use. It is an embedded system and should not use boost etc.
I see the following possibilities:
std::vector - drawbacks: The insertion at the end requires that all objects are copied and during this time another thread cannot access the vector. Edit: This can be avoided by implementing it as a circular buffer - see comments below. When iterating throught the vector, I have to test the place ID. Maybe it might also be a problem to allocate much memory as one block - because the memory could be segmented?
std::deque - compared to std::vector insertion (and pop_back) is faster but memory requirement? Iterators do not become invalid if the insertion is at the end. But I still have to iterate and test the second ID ("place"). I think it does not need to allocate all the memory in one big block as it is the case with vector or array. If an element is added in front and another one is removed at the end (or removed first and added after), I guess there does no memory allocation take place?
std::queue - instead of deque, I should rather use a queue? Is it true that in many implementations a queue ist implented just as a deque?
std::map - Like deque any iterators to existing elements will not become invalid. If I make the key a combination of place and timestamp, then iteration through the map is maybe faster because it is already sorted? Memory requirements of a map?
std::multimap - as the number of places is not constant I cannot make a multimap with "place" as the index.
std::list - has no advantage over deque here?
Some suggested the use of a circular buffer. If I do not want that the memory is allocated as one big block I still have to use a container and most questions above stay valid.
Update:
I will use a ring buffer as suggested here but using a deque as the underlying container. In order to being able to scroll fast through the datasets with the preselected "place" I will eventually introduce two additional indices into the data struct which will point to the previous and the next index with the same place.
How much memory will be used? In my special case the size of the struct is 56 bytes. The gnu lib uses 512 bytes as minimum block size, the IAR compiler 16 bytes. Hence the used block size will be 512 or 56 bytes respectively. Besides two iterators (using 4 pointers each) and the size there will be a pointer stored for each block. Therefore in the implementation of the iar compiler (block size 56 bytes) there will be 7 % overhead (on a 32 bit system) compared to the use of a std::vector or array. In the gcc implementation there will fit 9 objects in the block (504 bytes) while 512 + 4 bytes are needed per block which is 2 % more.
The block size is not large but the continuous memory size needed for the pointer array is already relatively large, especially for the implementation where one block is one struct.
A std::list would need 2 pointers per struct which is 14 % overhead in my case on 32 bit systems.
std::vector
... the memory could be segmented?
No, std::vector allocates contiguous memory, as is documented in that link. Arrays are also contiguous, but you might just as well use vector for this.
std::deque is segmented, which you said you didn't want. Or do you want to avoid a single large allocated block? It's not clear.
Anyway, it has no benefit over vector if you really want a circular buffer (because you'll never be adding/removing elements from the front/back anyway), and you can't control the block size.
std::queue
... Is it true that in many implementations a queue is implented just as a deque?
Yes, that's the default in all implementations. See the linked documentation or any decent book.
It doesn't sound like you want a FIFO queue, so I don't know why you're considering this one - the interface doesn't match your stated requirement.
'std::map`
... iteration through the map is maybe faster because it is already sorted?
On most modern server/desktop architectures, map will be slower because advancing an iterator involves a pointer chase (which impairs pipelining) and a likely cache miss. Your anonymous embedded architecture may be less sensitive to these effects, so map may be faster for you.
... Memory requirements of a map?
Higher. You have the node size (at least a couple of pointers) added to each element.

Can you predict where in memory a vector might move when growing?

I'm learning about C++ and have a conceptual question. Let's say I have a vector. I know that my vector is stored in contiguous memory, but let's say my vector keeps growing and runs out of room to keep the memory contiguous. How can I predict where in memory the vector will go? I'm excluding the option of using functions that tell the vector where it should be in memory.
If it "runs out of room to keep the memory contiguous", then it simply won't grow. Attempting to add items past the currently allocated size will (typically) result in its throwing an exception (though technically, it's up to the allocator object to decide what to do--it's responsible for memory allocation, and responding when that's not possible.
Note, however, that this could result from running out of address space (especially on a 32-bit machine) rather than running out of actual memory. A typical virtual memory manager can reallocate physical pages (e.g., 4 KB or 8 KB chunks) and write data to the paging file if necessary to free physical memory if needed--but when/if there's not enough contiguous address space, there's not much that can be done.
The answer depends highly on your allocation strategy, but in general, the answer is no. Most allocators do not provide you with information where the next allocation will occur. If you were writing a custom allocator, then you could potentially make this information accessible, but doing so is not necessarily a good idea unless your use case specifically requires this knowledge.
The realloc function is the only C function which will attempt to grow your memory in place, and it makes no guarantees that it will do so.
Neither new nor malloc provide any information for where the "next" allocation will take place. You could potentially guess, if you knew the exact implementation details for your specific compiler, but this would be very unwise to rely on in a real program. Regarding specifically the std::allocator used for std::vector, it also does not provide details about where future allocations will take place.
Even if you could predict it in a particular situation, it would be extremely fragile - all it takes is one function you call to change to make another call to new or malloc [unless you are using a very specific allocation method - which is different from the "usual" method] to "break" where the next allocation is made.
If you KNOW that you need a certain size, you can use std::vector::resize() to set the size of the vector [or std::vector<int> vec(10000); to create a pre-sized to 10000, for example] - which of course is not guaranteed to work, but it guarantees that you never need "enough space to hold 3x the current content", which is what happens with std::vector when you grow it using push_back [and if you are REALLY unlucky, that means that your vector will use 2*n-1 elements, leaving n-1 unused, because your size is n-1 and you add ONE more element, which doubles the size, so now 2*n, and you only actually require one more element...
The internal workings of STL containers are kept private for good reasons. You should never be accessing any container elements through any mechanism other than the appropriate iterators; and it is not possible to acquire one of those on an element that does not yet exist.
You could however, supply an allocator and use that to deterministically place future allocations.
Can you predict where in memory a vector might move when growing?
As others like EJP, Jerry and Mats have said, you cannot determine the location of a "grown" vector until after it grows. There are some corner cases, like the allocator providing a block of memory that's larger than required so that the vector does not actually move after a grow. But its not something you should depend on.
In general, stacks grow down and heaps grow up. This is an artifact from the old memory days. Your code segment was sandwiched between them, and it ensured your program would overwrite its own code segment and eventually cause an illegal instruction. So you might be able to guess the new vector is going to be higher in memory than the old vector because the vector is probably using heap memory. But its not really useful information.
If you are devising a strategy for locating elements after a grow, then use an index and not an iterator. Iterators are invalidated after inserts and deletes (including the grow).
For example, suppose you are parsing the vector and you are looking for the data that follows -----BEGIN CERTIFICATE-----. Once you know the offset of the data (byte 27 in the vector), then you can always relocate it in constant time with v.begin() + 26. If you only have part of the certificate and later add the tail of the data and the -----END CERTIFICATE----- (and the vector grows), then the data is still located at v.begin() + 26.
No, in practical terms you can't predict where it will go if it has to move due to resizing. However, it isn't so random that you could use it as a random number generator (;

Good container for appending chunks of memory to a continuous memory area

Is there any known header-only STL-like container/allocator for appending chunks of memory to another continuos memory area until it's filled? At the moment I am using a std::vector<char> vec, because it has some useful interface, but it's not optimal and somehow I think I am abusing it for my needs.
I first use std::vector::reserve to fix its capacity and allocate the required memory once for all to avoid unnecessary reallocations and then use std::copy(&chunk[0], &chunk[size], vec.data() + vec.size()) each time to append the new chunks of memory to the unfilled memory area behind the vector (of course size() <= capacity()). After each copy I explicitly update the size of the vector accordingly. Ok, I could use a back_inserter. But this not the point now (see below).
Of course std::copy could be specialized for char by any implementation so that it can just call memcpy at the end, but this is not a guarantee. Calling memcpy by myself to append the chunk to the memory already allocated by the vector to have such guarantee is just ugly. Are there better/more elegant options?
EDIT: I have no control on how the chunks of memory are allocated. They are given.
Basically the only way to "really" append memory to a contiguous memory area is to use the Posix function realloc(). Even with these allocated regions you can use std::copy, you only have to maintain knowledge about the end position in your region.
However, realloc() does not guarantee that the memory area will be at the previous memory location, but rather that the new block is fully contiguous. See man page for more details.
Few things to remember:
If you allocated memory via posix_memalign() it is not guaranteed that the memory alignment will be kept
There is no way to find out if the realloc() copied the data or not.
I know it's not exactly what you want, but std::deque usually stitches together contiguous blocks of memory.
There aren't any re-allocations as it grows, but the whole data may not be contiguous.
edit
Using a vector with preallocated memory, you can insert values at the end, which won't result in a reallocation unless the new values would make the size exceed the capacity:
vector<char> values(PRE_ALLOCATED_SIZE);
// ...
values.insert(values.end(), chunk, chunk+CHUNK_SIZE);
This probably is not what you're looking for, since they are designed for homogenous containers (i.e. where all the elements have the same type). I don't know if that fits your use case. On the off chance that you find it useful, I point you at:
get_temporary_buffer -- allocate raw storage (there's also a way to return the storage).
raw_storage_iterator -- output iterator over raw storage.
uninitialized_copy_n -- Copy construct several objects into raw storage (there is also a single element version).

Linked list vs dynamic array for implementing a stack using vector class

I was reading up on the two different ways of implementing a stack: linked list and dynamic arrays. The main advantage of a linked list over a dynamic array was that the linked list did not have to be resized while a dynamic array had to be resized if too many elements were inserted hence wasting alot of time and memory.
That got me wondering if this is true for C++ (as there is a vector class which automatically resizes whenever new elements are inserted)?
It's difficult to compare the two, because the patterns of their memory usage are quite different.
Vector resizing
A vector resizes itself dynamically as needed. It does that by allocating a new chunk of memory, moving (or copying) data from the old chunk to the new chunk, the releasing the old one. In a typical case, the new chunk is 1.5x the size of the old (contrary to popular belief, 2x seems to be quite unusual in practice). That means for a short time while reallocating, it needs memory equal to roughly 2.5x as much as the data you're actually storing. The rest of the time, the "chunk" that's in use is a minimum of 2/3rds full, and a maximum of completely full. If all sizes are equally likely, we can expect it to average about 5/6ths full. Looking at it from the other direction, we can expect about 1/6th, or about 17% of the space to be "wasted" at any given time.
When we do resize by a constant factor like that (rather than, for example, always adding a specific size of chunk, such as growing in 4Kb increments) we get what's called amortized constant time addition. In other words, as the array grows, resizing happens exponentially less often. The average number of times items in the array have been copied tends to a constant (usually around 3, but depends on the growth factor you use).
linked list allocations
Using a linked list, the situation is rather different. We never see resizing, so we don't see extra time or memory usage for some insertions. At the same time, we do see extra time and memory used essentially all the time. In particular, each node in the linked list needs to contain a pointer to the next node. Depending on the size of the data in the node compared to the size of a pointer, this can lead to significant overhead. For example, let's assume you need a stack of ints. In a typical case where an int is the same size as a pointer, that's going to mean 50% overhead -- all the time. It's increasingly common for a pointer to be larger than an int; twice the size is fairly common (64-bit pointer, 32-bit int). In such a case, you have ~67% overhead -- i.e., obviously enough, each node devoting twice as much space to the pointer as the data being stored.
Unfortunately, that's often just the tip of the iceberg. In a typical linked list, each node is dynamically allocated individually. At least if you're storing small data items (such as int) the memory allocated for a node may be (usually will be) even larger than the amount you actually request. So -- you ask for 12 bytes of memory to hold an int and a pointer -- but the chunk of memory you get is likely to be rounded up to 16 or 32 bytes instead. Now you're looking at overhead of at least 75% and quite possibly ~88%.
As far as speed goes, the situation is rather similar: allocating and freeing memory dynamically is often quite slow. The heap manager typically has blocks of free memory, and has to spend time searching through them to find the block that's most suited to the size you're asking for. Then it (typically) has to split that block into two pieces, one to satisfy your allocation, and another of the remaining memory it can use to satisfy other allocations. Likewise, when you free memory, it typically goes back to that same list of free blocks and checks whether there's an adjoining block of memory already free, so it can join the two back together.
Allocating and managing lots of blocks of memory is expensive.
cache usage
Finally, with recent processors we run into another important factor: cache usage. In the case of a vector, we have all the data right next to each other. Then, after the end of the part of the vector that's in use, we have some empty memory. This leads to excellent cache usage -- the data we're using gets cached; the data we're not using has little or no effect on the cache at all.
With a linked list, the pointers (and probable overhead in each node) are distributed throughout our list. I.e., each piece of data we care about has, right next to it, the overhead of the pointer, and the empty space allocated to the node that we're not using. In short, the effective size of the cache is reduced by about the same factor as the overall overhead of each node in the list -- i.e., we might easily see only 1/8th of the cache storing the date we care about, and 7/8ths devoted to storing pointers and/or pure garbage.
Summary
A linked list can work well when you have a relatively small number of nodes, each of which is individually quite large. If (as is more typical for a stack) you're dealing with a relatively large number of items, each of which is individually quite small, you're much less likely to see a savings in time or memory usage. Quite the contrary, for such cases, a linked list is much more likely to basically waste a great deal of both time and memory.
Yes, what you say is true for C++. For this reason, the default container inside std::stack, which is the standard stack class in C++, is neither a vector nor a linked list, but a double ended queue (a deque). This has nearly all the advantages of a vector, but it resizes much better.
Basically, an std::deque is a linked list of arrays of sorts internally. This way, when it needs to resize, it just adds another array.
First, the performance trade-offs between linked-lists and dynamic arrays are a lot more subtle than that.
The vector class in C++ is, by requirement, implemented as a "dynamic array", meaning that it must have an amortized-constant cost for inserting elements into it. How this is done is usually by increasing the "capacity" of the array in a geometric manner, that is, you double the capacity whenever you run out (or come close to running out). In the end, this means that a reallocation operation (allocating a new chunk of memory and copying the current content into it) is only going to happen on a few occasions. In practice, this means that the overhead for the reallocations only shows up on performance graphs as little spikes at logarithmic intervals. This is what it means to have "amortized-constant" cost, because once you neglect those little spikes, the cost of the insert operations is essentially constant (and trivial, in this case).
In a linked-list implementation, you don't have the overhead of reallocations, however, you do have the overhead of allocating each new element on freestore (dynamic memory). So, the overhead is a bit more regular (not spiked, which can be needed sometimes), but could be more significant than using a dynamic array, especially if the elements are rather inexpensive to copy (small in size, and simple object). In my opinion, linked-lists are only recommended for objects that are really expensive to copy (or move). But at the end of the day, this is something you need to test in any given situation.
Finally, it is important to point out that locality of reference is often the determining factor for any application that makes extensive use and traversal of the elements. When using a dynamic array, the elements are packed together in memory one after the other and doing an in-order traversal is very efficient as the CPU can preemptively cache the memory ahead of the reading / writing operations. In a vanilla linked-list implementation, the jumps from one element to the next generally involves a rather erratic jumps between wildly different memory locations, which effectively disables this "pre-fetching" behavior. So, unless the individual elements of the list are very big and operations on them are typically very long to execute, this lack of pre-fetching when using a linked-list will be the dominant performance problem.
As you can guess, I rarely use a linked-list (std::list), as the number of advantageous applications are few and far between. Very often, for large and expensive-to-copy objects, it is often preferable to simply use a vector of pointers (you get basically the same performance advantages (and disadvantages) as a linked list, but with less memory usage (for linking pointers) and you get random-access capabilities if you need it).
The main case that I can think of, where a linked-list wins over a dynamic array (or a segmented dynamic array like std::deque) is when you need to frequently insert elements in the middle (not at either ends). However, such situations usually arise when you are keeping a sorted (or ordered, in some way) set of elements, in which case, you would use a tree structure to store the elements (e.g., a binary search tree (BST)), not a linked-list. And often, such trees store their nodes (elements) using a semi-contiguous memory layout (e.g., a breadth-first layout) within a dynamic array or segmented dynamic array (e.g., a cache-oblivious dynamic array).
Yes, it's true for C++ or any other language. Dynamic array is a concept. The fact that C++ has vector doesn't change the theory. The vector in C++ actually does the resizing internally so this task isn't the developers' responsibility. The actual cost doesn't magically disappear when using vector, it's simply offloaded to the standard library implementation.
std::vector is implemented using a dynamic array, whereas std::list is implemented as a linked list. There are trade-offs for using both data structures. Pick the one that best suits your needs.
As you indicated, a dynamic array can take a larger amount of time adding an item if it gets full, as it has to expand itself. However, it is faster to access since all of its members are grouped together in memory. This tight grouping also usually makes it more cache-friendly.
Linked lists don't need to resize ever, but traversing them takes longer as the CPU must jump around in memory.
That got me wondering if this is true for c++ as there is a vector class which automatically resizes whenever new elements are inserted.
Yes, it still holds, because a vector resize is a potentially expensive operation. Internally, if the pre-allocated size for the vector is reached and you attempt to add new elements, a new allocation takes place and the old data is moved to the new memory location.
From the C++ documentation:
vector::push_back - Add element at the end
Adds a new element at the end of the vector, after its current last element. The content of val is copied (or moved) to the new element.
This effectively increases the container size by one, which causes an automatic reallocation of the allocated storage space if -and only if- the new vector size surpasses the current vector capacity.
http://channel9.msdn.com/Events/GoingNative/GoingNative-2012/Keynote-Bjarne-Stroustrup-Cpp11-Style
Skip to 44:40. You should prefer std::vector whenever possible over a std::list, as explained in the video, by Bjarne himself. Since std::vector stores all of it's elements next to each other, in memory, and because of that it will have the advantage of being cached in memory. And this is true for adding and removing elements from std::vector and also searching. He states that std::list is 50-100x slower than a std::vector.
If you really want a stack, you should really use std::stack instead of making your own.