Project GreenLight

This project, developing an instrument called GreenLight, measures, monitors, and optimizes the energy consumption of large-scale scientific applications from many different areas. The work enables inter-disciplinary researchers to understand how to make ?green? (i.e., energy efficient) decision for IT computation and storage. Consequently, an experienced team might be able to make deep and quantitative explorations in advanced architecture, including alternative circuit fabrics such as Field Programmable Gate Arrays (FPGAs), direct-graph execution machines, graphics processors, solid-state disks, and photonic networking. The enabled computing and systems research will yield new quantitative data to support engineering judgments on comparative? computational work per watt? across full-scale applications running at-scale computing platforms, thus helping to re-define fundamentals of systems engineering for a transformative concept, that of green CyberInfrastructure (CI). Keeping in mind that the IT industry consumes as much energy (same carbon footprint) as the airline industry, this project enables five communities of application scientists, drawn from metagenomics, ocean observing, microscopy, bioinformatics, and the digital media, to understand how to measure and then minimize energy consumption, to make use of novel energy/cooling sources, and employ middleware that automates optimal choice of compute/power strategies. The research issues addressed include studying the dynamic migration of applications to virtual machines for power consumption reduction, studying the migrations of virtual machines to physical machines to achieve network locality, developing new power/thermal management policies (closed loop, using feedback from sensors), classifying scientific algorithms in the context of co-processing hardware such as GPUs and FPGAs, and developing algorithms for resource sharing/scheduling in heterogeneous platforms. The full-scale virtualized device, the GreenLight Instrument, will be developed to measure, monitor, and make publicly available (via service-oriented architecture methodology), real-time sensor outputs, empowering researchers anywhere to study the energy cost of at-scale scientific computing. Hence, this work empowers domain application researchers to continue to exploit exponential improvements in silicon technology, and to compete globally. Although the IT industry has begun to develop strategies for ?greening? traditional data centers, the physical reality of modern campus CI currently involves a complex network of ad hoc and suboptimal energy environments in departmental facilities. The number of these facilities increases extremely fast creating campus-wide crisis of space, power, and cooling due to the value of computational and data-intensive approaches to research. This project addresses these important issues offering the possibility to improve.