Data organization for low power

Power consumption in relation to physical size of electronic hardware has increased as the components have become smaller and more densely packed.

In server systems, the study reveals that the memory consumes around 1.5 times the core power consumption.

Such redistribution of data by the compiler can significantly reduce energy consumption due to memory access.

[3] This method involves source code transformations that either modifies the data structure included in the source code or introduces new data structures or, possibly, modifies the access mode and the access paths with the aim of lowering power consumption.

This will typically reduce the energy consumption of the memory unit, because less area implies reduction in the total switched capacitance.

Current embedded processors particularly in the area of multimedia applications and graphic controllers have on-chip scratch pad memories.