Loop-size.md

+When vectorizing a loop, it is important to consider the number of loop iterations.
+It may not be worth vectorizing a loop that features a very small iteration count, since it can lead to underusing of the vector registers and may prove slower than the serial version.
+
+`PairLJCharmmCoulLong::compute` deals with interactions of pair of atoms `i,j`.
+The outer loop that traverses through the 32000 `i` atoms in the protein input.
+For each `i` atom, the inner loop traverses through atoms `j` that are neighbors of `i`.
+Moreover, each `i` atom can have a different amount of neighbors (`numneigh[i]`).
+
+Our optimization targets the vectorization of the inner loop, so its iteration count will determine if the loop is worth vectorizing.
+After modifying the code to print the number of inner loop iterations, we found that on average, the inner loop contains 375 iterations.
+Considering that registers in the 0.7 vector unit can hold up to 256 64-bit elements, the loop can be considered suitable for vectorizing iteration count wise.
+
+One can increase the number of iterations in the inner loop by increasing the neighbor distance threshold.
+This neighbor threshold is set automatically according to the interaction distance thresholds specified in the `pair_style lj/charmm/coul/long X Y` command.
+The largest interaction distance accepted by LAMMPS produced an average of 1290 inner loop iterations.
+It may be interesting to do some tests to see how higher inner loop iteration counts affect performance when comparing with the serial version.
+
+| input line | inner loop avg. iterations |
+| ---------- | -------------------------- |
+| `pair_style lj/charmm/coul/long 8.0 10.0` | 375 |
+| `pair_style lj/charmm/coul/long 8.0 16.1` | 1290|
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