DROP: Distributed Run-Time and Power Constraint Mapping for Many-Core Systems

The number of transistors per chip still steadily increases for each technology node generation. Fabrication processes and computing architectures have enabled the integration of hundreds of cores in the same chip leading to the design of many-core systems. Due to increased power and consequent thermal issues; power budget is a crucial constraint of computational resources. Consequently, only a subset of the available resources can be used at full throttle at any time, while the rest remain idle. Coping with increased power densities at run-time is a growing challenge in many-core systems. In this paper, we present a distributed run-time and power constraint mapping for many-core systems (DROP). The goal is to balance the power consumption in the platform. The model adopted is an agent-based power system for distributing power and managing Dynamic Frequency and Voltage (DVFS). In order to validate the model, we implemented our approach on a distributed shared memory system. The results show that the proposed methodology achieves a gain on an average of 28% in terms of mapping time.