There have been many proposals for sorting integers on multicores/GPUs that include radix-sort and its variants or other approaches that exploit specialized hardware features of a particular multicore architecture. Comparison-based algorithms have also been used. Network-based algorithms have also been used with primary example Batcher's bitonic sorting algorithm. Although such a latter approach is theoretically "inefficient", if there are few keys to sort, it can lead to better running times as it has low overhead and is simple to implement. In this work we perform an experimental study of integer sorting on multicore processors using not only multithreading but also multiprocessing parallel programming approaches. Our implementations work under Open MPI, MulticoreBSP, and BSPlib. We have implemented serial and parallel radix-sort for various radixes and also some previously little explored or unexplored variants of bitonic-sort and odd-even transposition sort. We offer our observations on a performance evaluation using the MBSP model of such algorithm implementations on multiple platforms and architectures and multiple programming libraries. If we can conclude anything is that modeling their performance by taking into consideration architecture dependent features such as the structure and characteristics of multiple memory hierarchies is difficult and more often than not unsuccessful or unreliable. However we can still draw some very simple conclusions using traditional architecture independent parallel modeling.