#Quicksort
##Inline partition vs method call for partitioning Result
Noticing somewhat significant difference between function call and inline partioning. Opting for using inline partitioning. ##Finding breakpoint between quicksort and insertion sort Try 1
Fixing bug in insertion sort.
Potential best break points: 7, 8, 10
Only using random pivot, broader range:
Potential best break points: 7, 9, 12, 15-19
Same test, for reproducability:
Selecting 12 as breaking point for insertion sort.
##Benchmark different pivot strategies with the chosen pivot vs Arrays.sort X axis denotes the number of elements for the given distribution of data and Y axis is number of nano seconds spent on average on each element in the array.
##Benchmarking with parallelized quicksort vs sequential quicksort Result
By parallelilizing the quicksort we get a significant performance improvement for random data but a small decrease in performance for the basic cases such as already sorted case.