Refactoring Conventional Task Schedulers to Exploit Asymmetric ARM big.LITTLE Architectures in Dense Linear Algebra

Dealing with asymmetry in the architecture opens a plethora of questions from the perspective of scheduling task-parallel applications for which there exist early ad-hoc strategies embedded into an asymmetry-conscious runtimes. In this paper we take a different path that addresses the complexity of the problem at the library level, via a few asymmetry-aware fundamental kernels, hiding the architecture heterogeneity from the task scheduler. For the specific domain of dense linear algebra, we show that this elegant solution delivers much higher performance than a naive approach based on an asymmetry-oblivious scheduler. Furthermore, this solution also outperforms an ad-hoc asymmetry-aware scheduler furnished with sophisticated scheduling techniques.