Address Code and Arithmetic Optimizations for Embedded Systems

An important class of problems used widely in both the embedded systems and scientific domains perform memory intensive computations on large data sets. These data sets get to be typically stored in main memory, which means that the compiler needs to generate the address of a memory location in order to store these data elements and generate the same address again when they are subsequently retrieved. This memory address computation is quite expensive, and if it is not performed efficiently, the performance degrades significantly. In this paper, we have developed a new compiler approach for optimizing the memory performance of subscripted or array variables and their address generation in stencil problems that are common in embedded image processing and other applications. Our approach makes use of the observation that in all these stencils, most of the elements accessed are stored close to one other in memory. We try to optimize the stencil codes with a view of reducing both the arit...

• Type: Conference
• Year: 2002
• Where: VLSID
• Authors: J. Ramanujam, Satish Krishnamurthy, Jinpyo Hong, Mahmut T. Kandemir
• Keywords: Address Computation Overhead, Computer Architecture, Memory Address Computation, Memory Intensive Computations, VLSID 2002