WCET-Aware Data Selection and Allocation for Scratchpad Memory

In embedded systems, SPM (scratchpad memory) is an attractive alternative to cache memory due to its lower energy consumption and higher predictability of program execution. This paper studies the problem of placing variables of a program into an SPM such that its WCET (worst-case execution time) is minimized. We propose an efficient dynamic approach that comprises two novel heuristics. The first heuristic iteratively selects a most beneficial variable as an SPM resident candidate based on its impact on the k longest paths of the program. The second heuristic incrementally allocates each SPM resident candidate to the SPM based on graph coloring and acyclic graph orientation. We have evaluated our approach by comparing with an ILP-based approach and a longest-path-based greedy approach using the eight benchmarks selected from Powerstone and Malardalen WCET Benchmark suites under three different SPM configurations. Our approach achieves up to 21% and 43% improvements in WCET reduction over the ILP-based approach and the greedy approach, respectively.