performance of matrix

Hello

so far, I used the scoring matrix [i] [k] in the 2D table calculations. Now, I came across another notation, which replaces table 2D in a 1 d table and consequently filling the individual items via matrix [I * j + k].

I wonder if the second approach is more effective? Obviously, dynamic memory allocation is simpler (and probably faster, too) in the case of vector, but what to access the items? Allocation of memory is actually only once, while in large networks, there may be millions of individual item operations...

Thanks for sharing your expertise!

Wolfgang

I think it depends on how you use the matrix.  Locality of reference can be more important than the calculation of pointer.

The 2D table is stored in the order of row field, then references along the line (through the columns if you want) and in adjacent rows, are fast, with fewer absences from the cache.  Similarly, the 1 d is in linear order, references in the vicinity will be faster, since the neighbouring location is more likely in the cache.

If access is distributed randomly in general the complete, I suspect that it does not have much if any difference which form matrix that you use, your application will spend more time to transfer data from main memory to the cache it will do the calculations of pointer.

I set up a 2D and accessed "against the grain" (along columns) and it has been considerably slower than access in the order of row field.  But then I was sequencing through all the matrix elements in all cases (no random access) so that it was important to do things.  And selection of the compiler was important, that the Visual Studio C++ compiler was the best to use.  The Intel C++ compiler would have been better if I had been able to use the vector instructions but linker CVI will not support the 16-byte alignment.

If you perform operations of full matrix with sequencing through all the elements of the matrix, you have other options for performance.  If your operation can be partitioned in the matrix, you can use multiple threads to simultaneously deal with the different sections of the matrix.

I assume that when you say the matrix do you mean a table of C of a numeric type, rather than a data structure special CVI supports - come to think of it, CVI does support matrices - but these can be simple C tables under the hood anyway.

Tags: NI Software

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