I'm working on a largish project, and we are having some memory issues now. Vectors have been used for all arrays, and a quick search there seems to be about 2000 member vectors.
Going through the code it seems nobody has ever used a reserve or a swap (were not on C++11 yet for this project).
Are there any tools or techniques I can do to find out how much memory is being lost in these vectors?
use valgrind for debugging memory issues.
http://valgrind.org/docs/manual/ms-manual.html
One fast but dirty trick to see the effect of capacity on memory would be to modify
std::vector (or typedef std::vector to your custom vector type).
Idea is to modify vector to ensure that this custom new vector increases capacity exactly by what is needed instead of doubling it (yes, it will be super slow), and see how memory usage of the application changes when you run it with this custom vector.
While not useful in actually optimizing the code, it at least quickly gives you an idea of how much you can gain by optimizing vectors.
Just add some periodic logging lines that print the vector size, capacity and
sizeof(v) + sizeof(element_type) * v.capacity();
for each of your vectors v (this last will be the exact size of the vector in memory). You could register all your vectors somewhere central to keep this tidy.
Then you can do some analysis by searching through your logfiles - to see which ones are using significant amounts of memory and how the usage varies over time. If it is only peak usage that is high, then you may be able to 'resize' your vectors to get rid of the spare capacity.
Related
I am making a chess engine, and have hit a brick wall with optimization. After using a profiler, I have found that the move generation is the biggest factor. When I looked closer, it turned out that a large portion of time generating moves was spent calling std::vector.push_back(move) when I had found a move.
Is there a way to have a dynamically sized c++ container that is fast? It can't be a fixed size array, as I have no way of knowing ahead of time how many moves will be generated (although there are usually less than 50).
Does anyone have experience with this sort of issue? I would write my own container if necessary, but I feel like there should be an standard way of doing this.
Call std::vector::reserve() with adequate size before the following push_back() calls to avoid memory re-allocation again and again.
Vector::reserve() helps. You can try to profile and see the distribution of number of moves, and try to reserve an optimal number in advance. Don't worry about memory waste because when you have 32 - 50 moves, the memory reserved might be 64, and there's a waste of 14 - 32. So reserve a memory of 8 or even 16 may not take much more memory.
Do you need to access moves by index? why not use std::list?
Or you can try to push_back a shared_ptr of a move, and then reserve some number in advance, there will be less memory waste.
Did you try profiling with std::deque? If you've no requirement that the objects be allocated in a contiguous fashion, then it might be an optimal solution. It provides constant time insert and erase to the front; usually std::deque is preferred if you need to insert or erase at both ends of the sequence.
You can read the details in GotW 54.
You can use std::vector and call its reserve method at appropriate places.
I use this method of profiling.
It doesn't surprise me that push_back is a big time-taker, and reserve should fix that.
However, if you profile again, you might find something else is the big time-taker, such as calls to new and delete for your move objects.
Fix that (by pooling), and do it again. Now, something else will be big.
Each time you do this, you get a speedup factor, and those factors multiply together, until you will be really pleased with the result.
I have a server that throughout the course of 24 hours keeps adding new items to a set. Elements are not deleted over the 24 period, just new elements keep getting inserted.
Then at end of period the set is cleared, and new elements start getting added again for another 24 hours.
Do you think a fast pool allocator would be useful here as to reuse the memory and possibly help with fragmentation?
The set grows to around 1 million elements. Each element is about 1k.
It's highly unlikely …but you are of course free to test it in your program.
For a collection of that size and allocation pattern (more! more! more! + grow! grow! grow!), you should use an array of vectors. Just keep it in contiguous blocks and reserve() when they are created and you never need to reallocate/resize or waste space and bandwidth traversing lists. vector is going to be best for your memory layout with a collection that large. Not one big vector (which would take a long time to resize), but several vectors, each which represent chunks (ideal chunk size can vary by platform -- I'd start with 5MB each and measure from there). If you follow, you see there is no need to resize or reuse memory; just create an allocation every few minutes for the next N objects -- there is no need for high frequency/speed object allocation and recreation.
The thing about a pool allocator would suggest you want a lot of objects which have discontiguous allocations, lots of inserts and deletes like a list of big allocations -- this is bad for a few reasons. If you want to create an implementation which optimizes for contiguous allocation at this size, just aim for the blocks with vectors approach. Allocation and lookup will both be close to minimal. At that point, allocation times should be tiny (relative to the other work you do). Then you will also have nothing unusual or surprising about your allocation patterns. However, the fast pool allocator suggests you treat this collection as a list, which will have terrible performance for this problem.
Once you implement that block+vector approach, a better performance comparison (at that point) would be to compare boost's pool_allocator vs std::allocator. Of course, you could test all three, but memory fragmentation is likely going to be reduced far more by that block of vectors approach, if you implement it correctly. Reference:
If you are seriously concerned about performance, use fast_pool_allocator when dealing with containers such as std::list, and use pool_allocator when dealing with containers such as std::vector.
I'm using a
vector<vector<size_t>> Ar;
structure. The contents of the structure change over time, and, in particular, the length of each of the nested vectors is random and changes in time. Order is important, and I cannot ignore the nested vector if it is empty. I know the maximum capacity of the nested vectors (say m) and outer vectors (say n).
I'm having some difficulty getting the initialization right. If I use
Ar(n);
there is no problem but I end up getting a memory fragmentation because the allocator does not know the size of nested vector. I would like to avoid this if possible, because I don't know what impact it will have as the size of the data I'm trying to handle increases. I try to get around the fragmentation by fixing the length of the nested vectors in advance to get a compact representation, but I'm having trouble doing this. I use
Ar(n,vector<size_t>(m));
but this is super slow and a massive waste of memory, because most of the entries will not be used.
I have successfully implemented this with a
vector<list<size_t> > Ar(n);
without suffering fragmentation, but it runs much slower than using a nested vector. A fixed representation such as a Boost::multi_array would take up too much space, for the same reason as the second initialization above, and it will be more difficult to implement because I would need to keep track of where the useful entries stop.
Any suggestions? Thanks in advance.
You don't know if memory fragmentation is a problem until you've profiled your code with a typical use case.
Unless m is very small in front of n, I think it won't be a bottleneck at all, since you still have mostly sequential memory accesses.
If you want to avoid it anyway, you could use reserve instead of resize or initialization with m objects. It will only allocate memory, without the overhead of constructing objects which will not be used, increasing initialization speed.
Moreover, reserveing capacity for the vectors will likely only consume virtual memory, not "real" memory, until you effectively use it.
And if you know the distribution of the inner vectors' size, use the mean value as the default length, it may help you reducing the waste of memory.
In any case, std::list is a bigger waste in space and a lot worse considering fragmentation.
Perhaps the resize function will help you. See here for details.
I have just read a question regarding initializing multidimensional vectors (question) and Viktor Sehr and Sbi reccomended instead using a single vector and getting the element with my_vector[x+y*100+z*100*100]. Why is this? Is it for performance reasons? If so, how does it improve performance? Thanks in advance, ell.
Edit: Do these reasons still apply when the width/height/depth are not the same and can change?
Just few reasons:
It wastes spaces, it is slow (unpredictable memory access, cache waste, etc), it's cumbersome
Main performance drawback is likely to be caching. With flat arrays you are guaranteed memory to be contiguous - cache is happy. With vector of vectors - who knows!
This advice is sound if you're looking at a bottleneck here. If memory usage or speed of access of this vector are not critical, just go down the easiest road.
You should have a look at Boost.MultiArray which gives you best of both worlds.
If for whatever reason you cannot use Boost, I'd definitely typedef it:
typedef vector<vector<vector<int> > > My3DIntVector;
My3DIntVector v;
…Viktor Sehr and Sbi reccomended instead using a single vector and getting the element with my_vector[x+y*100+z*100*100]. Why is this?
Given the dimensions, it's logical recommendation if the sizes are fixed.
Is it for performance reasons? If so, how does it improve performance?
Consider:
the number of allocations required to create all arrays
the time to copy even one dimension
the complexity it adds to the system's allocator
the time it takes to free
the complexity of common operations, such as filling
Edit: Do these reasons still apply when the width/height/depth are not the same and can change?
Resizing this (massive!) array can be extremely slow. You have to understand how your program will operate if you want it to be fastest. The copy and destruction complexity of elements is also a consideration (when using something more complex than int). If you do a lot of resizing or insertions/deletions, then the flattened vector can be very slow.
However, if its dimensions are fixed, you can do much better than std::vector. std::array is one alternative. (If you go the route of std::array, be careful of what you allocate on the stack)
The only thing I can imagine is that this is one big block of memory and thus prevents from fragmented memory. This is much easier to cache.
A vector<vector<vector<int> > > contains a lot of chunks of memory: a chunk for the first vector, a chunk for each element in vector<> and a chunk for each element in the vector<vector<>>. This is not easy to cache and may produce hardly predictable memory usage.
This might seem daft for which I'm sorry, I've been writing a bit some code for the Playstation 2 for uni. I am writing a sort of API for the Graphic Synthesizer. I am using a similar syntax to that of openGL which is a state machine.
So the input would something like
gsBegin(GS_TRIANGLE);
gsColor(...);
gsVertex3f(...);
gsVertex3f(...);
gsVertex3f(...);
gsEnd();
This is great so far for line/triangles/quads with a determined amount of vertices, however things like a LINE_STRIP or TRIANGLE_FAN take an undetermined amount of points. I have been warned off several times for using stl containers because of the push_back() method in this situation because of the time sensitive nature (is this justified).
If its not justified what would be a better way of dealing with the undetermined amount situation. Currently I have an Array that can hold 30 vertices at a time, is this best way of dealing with this kind of situation?
Vector's push_back has amortized constant time complexity because it exponentially increases the capacity of the vector. (I'm assuming you're using vector, because it's ideal for this situation.) However, in practice, rendering code is very performance sensitive, so if the push_back causes a vector reallocation, performance may suffer.
You can prevent reallocations by reserving the capacity before you add to it. If you call myvec.reserve(10);, you are guaranteed to be able to add 10 elements before the vector reallocates.
However, this still requires knowing ahead of time how many elements you need. Also, if you create and destroy lots of different vectors, you're still doing a lot of memory allocation. Instead, just use one vector for all vertices, and re-use it. Calling clear() returns it to empty while keeping its allocated capacity. This way you don't actually need to reserve anything - the first few times you use it it'll reallocate and grow, but once it reaches its peak size, it won't need to reallocate any more. The nice thing about this is the vector finds the approximate size it needs to be, and once it's "warmed up" there's no further allocation so it is high performance.
In short:
Use a single persistently stored std::vector
push_back as much as you like
When you're done, clear().
In practice this will perform as well as a C array, but without a hard limit on size.
University, eh? Just tell them push_back has amortized constant time complexity and they'll be happy.
First, avoid using glBegin / glEnd if you can, and instead use something like glDrawArrays or glDrawElements.
push_back() on a std::vector is a quick operation unless the array needs to grow in size when the operation occurs. Set the vector capacity as high as you think you will need it to be and you should see minimal overhead. 'Raw' arrays will usually always be slightly faster, but then you have to deal with using 'raw' arrays.
There is always the alternative of using a deque.
A deque is very much like a vector, contiguity apart. Basically, it's often implemented as a vector of arrays.
This means a lower allocation cost, but member access might be slightly slower (though constant) because of the double dereference, so I am unsure if it's profitable in your case.
There is also the LLVM alternative: SmallVector<T,N>, which preallocates (right in the vector) space for N elements, and will simply get back to using a traditional vector-like implementation once the size has grown too much.
The drawback to using std::vector in this kind of situation is making sure you manage your memory allocation properly. On systems like the PS2 (PS3 seems to be a bit better at this), memory allocation is insanely slow and if you don't reserve the right amount of space in the vector to begin with (and it has to resize several times when adding items), you will slow your game to a creeping crawl. If you know what your max size is going to be and reserve it when you create the vector, you won't have a problem.
That said, if this vector is going to be a temporary/local variable, you will still be reallocating memory every time your function is called. So if this function is called every frame, you will still have the performance problem. You can get around this by using a custom allocator and/or making the vector global (or a member variable to a class that will exist during your game loop).
You can always equip the container you want to use with proper allocator, which takes into account the limitations of the platform and the expected grow/shrink scenarios etc...