SIMD-Aware Loop Unrolling for Embedded Code Optimization

Due to the rising complexity of modern embedded media applications (EMAs), the instruction level parallelism (ILP) is not sufficient to meet the need. Compilers must have the capability to exploit the superword level parallelism (SLP), which can expose more concurrency lying in applications, minimize the latency created by memory access and hence produce more efficient codes. The loop is a good candidate for SLP extraction because of its paralleled structure between iterations. This work analyzes the memory access patterns found in EMAs and presents our method of loop unrolling to fully utilize these patterns to generate efficient Single Instruction Multiple Data (SIMD) instructions. Experimental results performed on TriMedia TM-1300 processor for the H.264 encoder show performance improvement by a factor ranging from 3 to 30 times with an average of 12 times.