Squashed commit of the sb-vbs branch.

Includes the SD-VBS benchmarks modified to:
- Use libextra to loop as realtime jobs
- Preallocate memory before starting their main computation
- Accept input via stdin instead of via argc

Does not include the SD-VBS matlab code.

Fixes libextra execution in LITMUS^RT.

1 files changed, 67 insertions, 0 deletions

diff --git a/SD-VBS/benchmarks/tracking/src/c/fillFeatures.c b/SD-VBS/benchmarks/tracking/src/c/fillFeatures.c
new file mode 100644
index 0000000..42de169
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/c/fillFeatures.c
@@ -0,0 +1,67 @@
+/********************************
+
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "tracking.h"
+
+/** Find the position and values of the top N_FEA features 
+        from the lambda matrix **/
+
+F2D* fillFeatures(F2D* lambda, int N_FEA, int win)
+{
+    int i, j, k, l;
+    int rows = lambda->height;
+    int cols = lambda->width;
+    F2D* features;
+
+        features = fSetArray(3, N_FEA, 0);
+
+        /** init array **/
+    for(i=0; i<N_FEA; i++)
+    {
+        subsref(features, 0, i) = -1.0;
+        subsref(features, 1, i) = -1.0;
+        subsref(features, 2, i) = 0.0;
+    }
+    
+
+        /** 
+                Find top N_FEA values and store them in 
+        features array along with row and col information 
+                It should be possible to make this algorithm better
+                if we use a pointer-based data structure,
+                but have not implemented due to MATLAB compatibility
+        **/ 
+
+        for (i=win; i<rows-win; i++)
+        {
+                for (j=win; j<cols-win; j++)
+                {
+            float currLambdaVal = subsref(lambda,i,j);
+                        if (subsref(features, 2, N_FEA-1) > currLambdaVal)
+                                continue;
+                        
+                        for (k=0; k<N_FEA; k++) 
+                        {
+                                if (subsref(features, 2, k) < currLambdaVal) 
+                                {
+                                        /** shift one slot **/
+                                        for (l=N_FEA-1; l>k; l--)
+                                        {
+                                                subsref(features, 0, l) = subsref(features, 0, l-1);
+                                                subsref(features, 1, l) = subsref(features, 1, l-1);
+                                                subsref(features, 2, l) = subsref(features, 2, l-1);
+                                        }       
+                                        
+                                subsref(features, 0, k) = j * 1.0;
+                                subsref(features, 1, k) = i * 1.0;
+                                subsref(features, 2, k) = currLambdaVal;
+                                        break;
+                                }
+                        }
+                }
+        }
+
+    return features;
+}