XPS: EXPL: FP: Symbiotic Power Management for Integrated CPU - GPU Platforms

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Power consumption is a major constraint on the operation of mobile computing devices. By reducing power consumption, it will be possible to prolong the operational time of battery operated devices. Modern computing devices integrate Central Processing Units (CPUs) and Graphic Processing Units (GPUs) on the same die to cater to the performance needs of various software applications. These software applications are usually written to execute parallel threads that make use of the CPUs and the GPUs. Integrated CPU-GPU devices offer many advantages over discrete CPU-GPU systems, including higher performance, reduced power consumption, and finer-grained interactions between the CPU and GPU.The overarching goal of this proposal is to explore a new paradigm for symbiotic power management that exploits the structure and semantics of parallel programming languages for CPU-GPU devices to deliver improved power management capabilities. To achieve this goal, the PI will first identify the operational phases of software applications directly from their parallel programming constructs, and then use the identified phases to devise an adaptive power management method that determines the optimal resources (e.g., frequency-voltage settings and number of cores) to meet performance targets while offering large reductions in power consumption. In synergy with the overarching goal, the PI will pursue an educational outreach program that includes: expanding on-going projects targeted for local high-school students to increase their knowledge of energy challenges in computing systems; developing courses on high-performance computing systems; involving undergraduate students in research experiences; and outreach to industry.