Run-time heterogeneous-aware power-adaptive scheduling in OpenFOAM

Abstract

Computer-Aided engineering simulations, in particular, Computational Fluid Dynamics, have become a fundamental design and analysis tool in product development. Over time, a demand for larger problem sizes and higher accuracy has led to huge computational workloads requiring extended compute capabilities. Increasing computing capabilities requirements, however, drive a fast-growing power consumption. In order to deal with increasing power demand, hardware and software solutions' reevaluation in terms of power-efficiency becomes of paramount importance. Establishing a power budget and reducing the compute units operating frequency in order to comply with such budget is becoming common practice. However, in the presence of heterogeneous compute units and dynamic workloads, a static and uniform reduction across compute units leads to a potentially severe impact on performance. This paper proposes a run-Time heterogeneity-Aware power-Adaptive schedule that provides power consumption optimization, targeting heterogeneous parallel distributed systems in the context of CFD simulations. The proposed approach is integrated into OpenFOAM computational library and explores power migration and reduction across nodes, considering runtime workload imbalances and node performances. Results reveal not only a substantial reduction in power usage but also significant performance gains relative to the uniform static approach. To the best of authors' knowledge, this is the first implementation and integration of power management solutions in OpenFOAM.