I've got a Lua program that seems to be slower than it ought to be. I suspect the issue is that I'm adding values to an associative array one at a time and the table has to allocate new memory each time.
There did seem to be a table.setn function, but it fails under Lua 5.1.3:
stdin:1: 'setn' is obsolete
stack traceback:
[C]: in function 'setn'
stdin:1: in main chunk
[C]: ?
I gather from the Google searching I've done that this function was depreciated in Lua 5.1, but I can't find what (if anything) replaced the functionality.
Do you know how to pre-size a table in Lua?
Alternatively, is there some other way to avoid memory allocation when you add an object to a table?
Let me focus more on your question:
adding values to an associative array
one at a time
Tables in Lua are associative, but using them in an array form (1..N) is optimized. They have double faces, internally.
So.. If you indeed are adding values associatively, follow the rules above.
If you are using indices 1..N, you can force a one-time size readjust by setting t[100000]= something. This should work until the limit of optimized array size, specified within Lua sources (2^26 = 67108864). After that, everything is associative.
p.s. The old 'setn' method handled the array part only, so it's no use for associative usage (ignore those answers).
p.p.s. Have you studied general tips for keeping Lua performance high? i.e. know table creation and rather reuse a table than create a new one, use of 'local print=print' and such to avoid global accesses.
static int new_sized_table( lua_State *L )
{
int asize = lua_tointeger( L, 1 );
int hsize = lua_tointeger( L, 2 );
lua_createtable( L, asize, hsize );
return( 1 );
}
...
lua_pushcfunction( L, new_sized_table );
lua_setglobal( L, "sized_table" );
Then, in Lua,
array = function(size) return sized_table(size,0) end
a = array(10)
As a quick hack to get this running you can add the C to lua.c.
I don't think you can - it's not an array, it's an associative array, like a perl hash or an awk array.
http://www.lua.org/manual/5.1/manual.html#2.5.5
I don't think you can preset its size meaningfully from the Lua side.
If you're allocating the array on the C side, though, the
void lua_createtable (lua_State *L, int narr, int nrec);
may be what you need.
Creates a new empty table and pushes
it onto the stack. The new table has
space pre-allocated for narr array
elements and nrec non-array elements.
This pre-allocation is useful when you
know exactly how many elements the
table will have. Otherwise you can use
the function lua_newtable.
There is still an internal luaL_setn and you can compile Lua so that
it is exposed as table.setn. But it looks like that it won't help
because the code doesn't seem to do any pre-extending.
(Also the setn as commented above the setn is related to the array part
of a Lua table, and you said that your are using the table as an associative
array)
The good part is that even if you add the elements one by one, Lua does not
increase the array that way. Instead it uses a more reasonable strategy. You still
get multiple allocations for a larger array but the performance is better than
getting a new allocation each time.
Although this doesn't answer your main question, it answers your second question:
Alternatively, is there some other way to avoid memory allocation when you add an object to a table?
If your running Lua in a custom application, as I can guess since your doing C coding, I suggest you replace the allocator with Loki's small value allocator, it reduced my memory allocations 100+ fold. This improved performance by avoiding round trips to the Kernel, and made me a much happier programmer :)
Anyways I tried other allocators, but they were more general, and provide guarantee's that don't benefit Lua applications (such as thread safety, and large object allocation, etc...), also writing your own small-object allocator can be a good week of programming and debugging to get just right, and after searching for an available solution Loki's allocator wasthe easiest and fastest I found for this problem.
If you declare your table in code with a specific amount of items, like so:
local tab = { 0, 1, 2, 3, 4, 5, ... , n }
then Lua will create the table with memory already allocated for at least n items.
However, Lua uses the 2x incremental memory allocation technique, so adding an item to a table should rarely force a reallocation.
Related
Is it okay to create a single FFTSetup data structure and use it to perform multiple FFT computations concurrently? Would something like the following work?
FFTSetup fftSetup = vDSP_create_fftsetup(
16, // vDSP_Length __vDSP_log2n,
kFFTRadix2 // FFTRadix __vDSP_radix
);
NSAssert(fftSetup != NULL, #"vDSP_create_fftsetup() failed to allocate storage");
for (int i = 0; i < 100; i++)
{
dispatch_async(dispatch_get_global_queue(DISPATCH_QUEUE_PRIORITY_HIGH, 0),
^{
vDSP_fft_zrip(
fftSetup, // FFTSetup __vDSP_setup,
&(splitComplex[i]), // DSPSplitComplex *__vDSP_ioData,
1, // vDSP_Stride __vDSP_stride,
16, // vDSP_Length __vDSP_log2n,
kFFTDirection_Forward // FFTDirection __vDSP_direction
);
});
}
I suppose that the answer depends on the following considerations:
1) Does vDSP_fft_zrip() only access the data within fftSetup (or the data pointed to by it) in a "read-only" fashion? Or are there perhaps some temporary buffers (scratch space) within fftSetup that is written to by vDSP_fft_zrip() in performing its FFT computations?
2) If data like that in fftSetup is being accessed in a "read-only" fashion, is it okay for multiple processes/threads/tasks/blocks to access it simultaneously? (I am thinking of the case where it is possible for more than one process to open the same file for reading, though not necessarily for writing or appending. Is this analogy appropriate?)
On a related note, just how much memory is being taken up by the FFTSetup data structure? Is there any way to find out? (It is an opaque data type.)
You may create one FFT setup and use it repeatedly and concurrently. This is the intended use. (I am the author of the current implementations of vDSP_fft_zrip and other FFT implementations in vDSP.)
In Using Fourier Transforms we're told that the FFTSetup contains the FFT weight array which is a series of complex exponentials. The vDSP_create_fftsetup documentation says
Once prepared, the setup structure can be used repeatedly by FFT
functions (which read the data in the structure and do not alter it)
for any (power of two) length up to that specified when you created
the structure.
so
conceptually, vDSP_fft_zrip should not need to modify the weight array and so it would appear to be one of the FFT functions that do not alter the FFTSetup (I haven't seen any that do apart from create/destroy), however there are no guarantees on what the actual implementation does - it could do anything.
if vDSP_fft_zrip truly accesses its FFTSetup in a read-only fashion, then it's fine to do that from multiple threads.
As for memory usage, the FFT weight array is e^{i*k*2*M_PI/N} for k = [0..N-1], which are N complex float values, so that would 2*N*sizeof(float).
But those complex exponentials are very symmetric so who knows, under the hood the implementation could require less memory. Or more!
In your case, N = 2^16, so it wouldn't be strange to see up to 256k being used.
Where does that leave you? I think it seems reasonable that the FFTSetup be accessible from multiple threads, but it appears to be undocumented. You could be lucky. Or unlucky and unpleasantly surprised now or in a future version of the framework.
So... do you feel lucky?
I wouldn't attempt any explicit concurrency with the vDSP functions, or any other function in the Accelerate framework (of which vDSP is a part) for that matter. Why? Because Accelerate is already designed to take advantage of multiple cores, as well as specific nuances of a given processor implementation, on your behalf - see http://developer.apple.com/library/mac/#DOCUMENTATION/Darwin/Reference/ManPages/man7/vecLib.7.html. You may end up essentially re-parallelizing already parallel computations that are internal to the implementation (if not now, then possibly in a later version). The best approach to the Accelerate framework is generally to assume that it's more clever than you are and just use it in the simplest way possible, then do your performance measurements. If those measurements reflect a level of performance that is somehow insufficient for your needs, then try your own optimizations (and/or file a bug report against the Accelerate framework at http://bugreport.apple.com since the authors of that framework are always interested in knowing where or if their efforts somehow fell short of developer requirements).
I have a program in VB.net that uses a 3D array:
Private gridList(10, 900, 900) As GridElement
Now, I just used a Memory Profiler on it (because my application is having some major leak issues or something) and apparently, this array (containing at the moment of testing 0-30 elements at one time) is using 94% of the memory currently in use by my application. Even when it is empty it takes up huge amounts of memory.
My only assumption is that even empty arrays take up space! This puts a major blow into my plans!
My Question:
Is there any alternative to this that allows me to still have the same abilities to map
i.g. I've been using it like this:
Dim cGE as GridElement = gridList(3, 5, 7)
but doesn't hog up so much memory for things that aren't using memory?
Thanks!
Do Arrays take up space even without values in them in .net?
No. But your array has values in it. And hence takes up space.
To avoid keeping a lot of elements in memory when you only access a few of all the possible elements, you need to use a so-called sparse array. In .NET, this is easiest implemented via a Dictionary, where the key in your case would be a three-element structure*, and the value would be a GridElement.
* If you’re using an up-to-date version of .NET, then you can model this via a Tuple(Of Integer, Integer, Integer)
I didn't think it fair to post a comment on Fredrik Mörk's answer in this 2 year old post, so I thought I'd just ask it as a new question instead...
NB: This is not a critiscm of the answer in any way, I'm simply trying to understand this all before delving into memory management / the marshal class.
In that answer, the function GetByteArray allocates memory to each object within the given array, within a loop.
Would the GetByteArray function on the aforementioned post have benefited at all from allocating memory for the total size of the provided array:
Dim arrayBufferPtr = Marshal.AllocHGlobal(Marshal.SizeOf(<arrayElement>) * <array>.Count)
I just wonder if allocating the memory, as shown in the answer, causes any kind of fragmentation? Assuming there may be fragmentation, would there be much of an impact to be concerned with? Would allocating the memory in the way I've shown force you to call IntPtr.ToInt## to obtain pointer offsets from the overall allocation pointer, and therefore force you to check the underlying architecture to ensure the correct method is used*1 or is there a better way? (ToInt32/ToInt64 depending on x86/64?)
*1 I read elsewhere that calling the wrong IntPtr.ToInt## will cause overflow exceptions. What I mean by that statement is would I use:
Dim anOffsetPtr As New IntPtr(arrayBufferPtr.ToInt## + (loopIndex * <arrayElementSize>))
I've read through a few articles on the VB.Net Marshal class and memory allocation; listed below, but if you know fo any other good articles I'm all ears!
http://msdn.microsoft.com/en-us/library/system.runtime.interopservices.marshal.aspx
http://www.dotnetbips.com/articles/44bad06d-3662-41d3-b712-b45546cd8fa8.aspx
My favourite so far:
http://www.codeproject.com/KB/vb/Marshal.aspx
It is possible to allocate unmanaged memory for the whole array, and then copy every array element with SizeOf(arrayElement)*loopIndex offset. It is better to use appropriate ToInt32/ToInt64 method, according to the current platform, like:
Dim anOffsetPtr
if arrayBufferPtr.Size = 4 then
anOffsetPtr = New IntPtr(arrayBufferPtr.ToInt32() + (loopIndex * arrayElementSize))
else
anOffsetPtr = New IntPtr(arrayBufferPtr.ToInt64() + (loopIndex * arrayElementSize))
endif
For fast MTF ( http://en.wikipedia.org/wiki/Move-to-front_transform ) i need faster version of moving a char from inside the array into the front of it:
char mtfSymbol[256], front;
char i;
for(;;) { \\ a very big loop
...
i=get_i(); \\ i is in 0..256 but more likely to be smaller.
front=mtfSymbol[i];
memmove(mtfSymbol+1, mtfSymbol, i);
mtfSymbol[0]=front;
}
cachegrind shows, that for memmove there are lot of branch mispredictions here.
For the other version of code (not a memmove in the first example, but this one)
do
{
mtfSymbol[i] = mtfSymbol[i-1];
} while ( --i );
there are lot of byte reads/writes, conditional branches and branch mispredictions
i is not very big, as it is MTF used for "good" input - a text file after a BWT ( Burrows–Wheeler transform )
Compiler is GCC.
If you pre-allocate your buffer bigger than you're going to need it, and put your initial array somewhere in the middle (or at the end, if you're never going to have to extend it that way) then you can append items (up to a limit) by changing the address of the start of the array rather than by moving all the elements.
You'll obviously need to keep track of how far back you've moved, so you can re-allocate if you do fall off the start of your existing allocation, but this should still be quicker than moving all of your array entries around.
You can also use a dedicated data structure rather than an array to speed up the forward transform.
A fast implementation can be built with a list of linked lists to avoid the array element moves altogether.
See http://code.google.com/p/kanzi/source/browse/java/src/kanzi/transform/MTFT.java
For inverse transform, it turns out that arrays are as fast as linked lists.
I'm implementing a trie for predictive text entry in VB.NET - basically autocompletion as far as the use of the trie is concerned. I've made my trie a recursive data structure based on the generic dictionary class.
It's basically:
class WordTree Inherits Dictionary(of Char, WordTree)
Each letter in a word (all upper cased) is used as a key to a new WordTrie. A null character on a leaf indicates the termination of a word. To find a word starting with a prefix I walk the trie as far as my prefix goes then collect all children words.
My question is basically on the implementation of the trie itself. I'm using the dictionary hash function to branch my tree. I could use a list and do a linear search over the list, or do something else. What's the smooth move here? Is this a reasonable way to do my branching?
Thanks.
Update:
Just to clarify, I'm basically asking if the dictionary branching approach is obviously inferior to some other alternative. The application in which I'm using this data structure only uses upper case letters, so maybe the array approach is the best. I might use the same data structure for a more complex typeahead situation in the future (more characters). In that case, it sounds like the dictionary is the right approach - up to the point where I need to use something more complex in general.
If it's just the 26 letters, as a 26 entry array. Then lookup is by index. It probably uses less space than the Dictionary if the bucket-list is longer than 26.
If you are worried about space, you can use bitmap compression on the valid byte transitions, assuming the 26char limit.
class State // could be struct or whatever
{
int valid; // can handle 32 transitions -- each bit set is valid
vector<State> transitions;
State getNextState( int ch )
{
int index;
int mask = ( 1 << ( toupper( ch ) - 'A' )) -1;
int bitsToCount = valid & mask;
for( index = 0; bitsToCount ; bitsToCount >>= 1)
{
index += bitsToCount & 1;
}
transitions.at( index );
}
};
There are other ways to do the bit counting Here, the index into the vector is the number of set bits in the valid bitset. the other alternative is the direct indexed array of states;
class State
{
State transitions[ 26 ]; // use the char as the index.
State getNextState( int ch )
{
return transitions[ ch ];
}
};
A good data structure that's efficient in space and potentially gives sub-linear prefix lookups is the ternary search tree. Peter Kankowski has a fantastic article about it. He uses C, but it's straightforward code once you understand the data structure. As he mentioned, this is the structure ispell uses for spelling correction.
I have done this (a trie implementation) in C with 8 bit chars, and simply used the array version (as alluded to by the "26 chars" answer).
HOWEVER, I am guessing that you want full unicode support (since a .NET char is unicode, among other reasons). Assuming you have to have support for unicode, the hash/map/dictionary lookup is probably your best bet, as a 64K entry array in each node won't really work very well.
About the only hack up I could think of on this is to store entire strings (suffixes or possibly "in-fixes") on branches that do not yet split, depending on how sparse the tree, er, trie, is. That adds a lot of logic to detect the multi-char strings, though, and to split them up when an alternate path is introduced.
What is the read vs update pattern?
---- update jul 2013 ---
If .NET strings have a function like java to get the bytes for a string (as UTF-8), then having an array in each node to represent the current position's byte value is probably a good way to go. You could even make the arrays variable size, with first/last bounds indicators in each node, since MANY nodes will have only lower case ASCII letters anyway, or only upper case letters or the digits 0-9 in some cases.
I've found burst trie's to be very space efficient. I wrote my own burst trie in Scala that also re-uses some ideas that I found in GWT's trie implementation. I used it in Stripe's Capture the Flag contest on a problem that was multi-node with a small amount of RAM.