Performance-influencing Factors for Parallel and Algorithmic Problems in Multicore Environments: Work-In-Progress Paper

Model-based approaches in Software Performance Engineering (SPE) are used in early design phases to evaluate performance. Most current model-based prediction approaches work quite well for single-core CPUs but are not suitable or precise enough for multicore environments. This is because they only consider a single metric (i.e., the CPU speed) as a factor affecting performance. Therefore, we investigate parallel-performance-influencing factors (PPIFs) as a preparing step to improve current performance prediction models by providing references curves for the speedup behaviour of different resource demands and scenarios. In this paper, we show initial results and their relevance for future work.