  The analysis of algorithms mostly relies on counting classic elementary
operations like additions, multiplications, comparisons, swaps etc. This
approach is often sufficient to quantify an algorithm's efficiency. In some
cases, however, features of modern processor architectures like pipelined
execution and memory hierarchies have significant impact on running time and
need to be taken into account to get a reliable picture. One such example is
Quicksort: It has been demonstrated experimentally that under certain
conditions on the hardware the classically optimal balanced choice of the pivot
as median of a sample gets harmful. The reason lies in mispredicted branches
whose rollback costs become dominating.
  In this paper, we give the first precise analytical investigation of the
influence of pipelining and the resulting branch mispredictions on the
efficiency of (classic) Quicksort and Yaroslavskiy's dual-pivot Quicksort as
implemented in Oracle's Java 7 library. For the latter it is still not fully
understood why experiments prove it 10% faster than a highly engineered
implementation of a classic single-pivot version. For different branch
prediction strategies, we give precise asymptotics for the expected number of
branch misses caused by the aforementioned Quicksort variants when their pivots
are chosen from a sample of the input. We conclude that the difference in
branch misses is too small to explain the superiority of the dual-pivot
algorithm.

Data Structures and Algorithms;Probability