Integrated Layer Processing (ILP) has been presented as an implementation technique to improve communication protocol performance by reducing the number of memory references. Previous research has however not pointed out that in some circumstances ILP can significantly increase the number of memory references, resulting in lower communication throughput. We explore the performance effects of applying ILP to data manipulation functions with varying characteristics. The functions are generated from a set of parameters including input and output block size, state size and number of instructions. We present experimental data for varying function state sizes, number of integrated functions and instruction counts. The results clearly show that the aggregated state of the functions must fit in registers for ILP to be competitive.