A Multilevel Introspective Dynamic Optimization System For Holistic Power-Aware Computing

Power consumption is rapidly becoming the dominant limit- ing factor for further improvements in computer design. Curiously, this applies both at the "high-end" of workstations and servers and the "low end" of handheld devices and embedded computers. At the high-end, the challenge lies in dealing with exponentially growing power densities. At the low-end, there is a demand to make mobile devices more powerful and longer lasting, but battery technology is not improving at the same rate that power consumption is rising. Traditional power-management research is fragmented; techniques are being developed at specific levels, without fully exploring their synergy with other levels. Most software techniques target either operating systems or compilers but do not ex- plore the interaction between the two layers. These techniques also have not fully explored the potential of virtual machines for power manage- ment. In contrast, we are developing a system that integrates information from multiple levels of software and hardware, connecting these levels through a communication channel. At the heart of this system are a virtual ma- chine that compiles and dynamically profiles code, and an optimizer that reoptimizes all code, including that of applications and the virtual ma- chine itself. We believe this introspective, holistic approach enables more informed power-management decisions.