A growing number of energy optimization solutions operate at the application runtime level. Despite delivering promising results, these application-scoped optimizations are fundamentally greedy: They assume to have an exclusive access to power management and often perform poorly when multiple power-managing applications co-exist, or different threads of the same application share power management hardware. In this paper, we introduce AEQUITAS, a first step to address this critical yet largely overlooked problem. The insight behind AEQUITAS is that co-existing applications may view power-managing hardware as a shared resource and coordinate power management decisions. As a concrete instance of this philosophy, we evaluated our ideas on top of a state-of-the-art energy-efficient work-stealing runtime. Experiments show that without AEQUITAS, multiple co-existing power-managing application runtimes suffer up to 32% performance loss and negate all power savings. With AEQUITAS, the beneficial energy-performance tradeoff reported in the single-application setting (12.9% energy savings and 2.5% performance loss) can be retained, but in a much more challenging setting where multiple power-managing runtimes co-exist on parallel architectures and multiple CPU cores share the same power domain.

Work stealing is a promising approach to constructing multithreaded program runtimes of parallel programming languages. This paper presents HERMES, an energy-efficient work-stealing language runtime. The key insight is that threads in a work-stealing environment -- thieves and victims - have varying impacts on the overall program running time, and a coordination of their execution "tempo" can lead to energy efficiency with minimal performance loss. The centerpiece of HERMES is two complementary algorithms to coordinate thread tempo: the workpath-sensitive algorithm determines tempo for each thread based on thief-victim relationships on the execution path, whereas the workload-sensitive algorithm selects appropriate tempo based on the size of work-stealing deques. We construct HERMES on top of Intel Cilk Plus's runtime, and implement tempo adjustment through standard Dynamic Voltage and Frequency Scaling (DVFS). Benchmarks running on HERMES demonstrate an average of 11-12% energy savings with an average of 3-4% performance loss through meter-based measurements over commercial CPUs.