Madagascar Code Patterns

From Madagascar

All patterns are in C, unless otherwise noted.

Contents 1 Loop over ensembles 2 I/O-optimized loop over samples 2.1 Description and usage 2.2 Example 2.3 Potential for improvement 3 OMP parallelized loop 3.1 Description and usage 3.2 Example 3.3 Potential for improvement 4 Parallelized, I/O-optimized loop over samples 4.1 Description and usage 4.2 Example 4.3 Potential for improvement

Loop over ensembles

This is a simple loop over reading 1-D arrays ("traces"), 2-D ("gathers"), etc.

It is necessary in the case of algorithms that act on one ensemble at a time. Parallelizable with OMP.

I/O-optimized loop over samples

Description and usage

It consists of looping over an entire dataset and applying a given procedure to every single sample in a dataset, regardless of what "trace"/"frame"/"volume" it belongs to. Example: computing the sum of all elements of a dataset; computing a histogram; performing a clip operation; etc. It uses the BUFSIZ macro defined in stdio.h to ensure efficient stream I/O. Its occurences can be easily found by grepping for BUFSIZ in the codebase.

Example

int n; /* Total number of elements in dataset */
int nbuf; /* Number of elements in I/O buffer */
float *fbuf; /* I/O array */
sf_file in=NULL; /* Input file. Here is stdin, but this is not compulsory */
 
in = sf_input("in");
 
n = sf_filesize(in);
 
/* This example uses float as data type. 
Any other data type (int, sf_complex, etc) can be used, as appropriate */
nbuf = BUFSIZ/sizeof(float);
 
fbuf = sf_floatalloc(nbuf);
 
for (; n > 0; n -= nbuf) {
 
    if (nbuf > n) nbuf = n;
 
    sf_floatread(fbuf, nbuf, in);
 
    for (i=0; i < nbuf; i++) {
        /* Do computations here */
    }
}

Potential for improvement

This pattern should be parallelized using OpenMP.

The GNU C Library documentation states that when doing I/O on a file (as opposed to a stream), the st_blksize field of the file attributes is a better choice than BUFSIZ.

OMP parallelized loop

Description and usage

Shared-memory parallelization using the OpenMP library.

Example

Potential for improvement

Parallelized, I/O-optimized loop over samples

Description and usage

Example

Potential for improvement