DRDU: A data reuse analysis technique for efficient scratch-pad memory management
In multimedia and other streaming applications, a significant portion of energy is spent on data transfers. Exploiting data reuse opportunities in the application, we can reduce this energy by making copies of frequently used data in a small local memory and replacing speed- and power-inefficient transfers from main off-chip memory by more efficient local data transfers. In this article we present an automated approach for analyzing these opportunities in a program that allows modification of the program to use custom scratch-pad memory configurations comprising a hierarchical set of buffers for local storage of frequently reused data. Using our approach we are able to both reduce energy consumption of the memory subsystem when using a scratch-pad memory by about a factor of two, on average, and improve memory system performance compared to a cache of the same size.
data reuse analysis scratch-pad memory management performance design algorithms memory hierarchy compiler analysis