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08/16/2002 at 05:19AM PDT, ID: 20337349
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8.2

help on C++ optimization

Asked by qocarlos in C++ Programming Language

Tags: optimization, row

I'm doing some specialized processing on data matrices.
 Typically, I use to
 allocate one dimensional arrays for my 2D matrices and then I
 just need to
 use pointer arithmetic to access to any element in the
 matrix. For example,
 in the case of a matrix of nRows and nCols, the matrix is allocated as
 follows:
 
  loat* fM = new float[nCols * nRows];
 
  Then, for example, to modify all the elements of row #5 of a
  matrix, the
  code could be something like this:
 
  int nOffset = 5 * nCols;
  float*f = fM + nOffset;
  for (register int i = 0; i < nCols; i++, f++)
       *f = whatever;
 
  On the other hand, in order to modify all the elements of a
  given column
  (i.e. column # 5) the code would be:
 
  float*f = fM + 5;
  for (register int i = 0; i < nRows; i++, f += nRows)
       *f = whatever;
 
  I found that operations performed along rows are much faster than
  operations performed along the columns. I understand that
  this is because  elements on rows are contiguous in memory whilst elements in
  columns are  separated by the number of columns of each row. Perhaps the CPU is caching memory so that it is faster to access nearby
memory locations.
  I would like to speed up the processing along columns. I have read
  somewhere that one way would be to process 8 columns together. This is
  effective if the processor contains 64 registers, which I
  guess most modern
  processors have. However, I can't find that information
  anymore and I can't  figure out how to process 8 columns at the same time. Do you have any
  experience on this sort of optimizations issues?
  Thanks for your help,
[+][-]08/16/02 10:03 AM, ID: 7225206

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[+][-]08/16/02 11:37 AM, ID: 7225357

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[+][-]08/20/02 04:21 PM, ID: 7232271

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Zone: C++ Programming Language
Tags: optimization, row
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Solution Provided By: DanRollins
Participating Experts: 3
Solution Grade: A
 
 
[+][-]08/20/02 05:04 PM, ID: 7232312

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