MRI: Development of Instrumentation for Project GreenLight

提案号：CNS 08-21155PI(s): DeFanti, Thomas A. Krueger, Ingolf H.；菲利普·m·帕帕佐普洛斯；Larry L. Smarr；毕业院校：加州大学？圣地亚哥La Jolla， CA 92093-0934题目：MRI/Dev。项目建议：该项目开发一种名为GreenLight的仪器，用于测量、监测和优化来自许多不同领域的大规模科学应用的能耗。这项工作使跨学科研究人员能够了解如何使“绿色”（即，能源效率）决策的IT计算和存储。因此，经验丰富的团队可能能够对高级架构进行深入和定量的探索，包括替代电路结构，如现场可编程门阵列（fpga）、直接图形执行机、图形处理器、固态磁盘和光子网络。启用的计算和系统研究将产生新的定量数据，以支持对比较？每瓦特的计算功？通过在大规模计算平台上运行的全面应用程序，从而帮助重新定义系统工程的基本原理，以实现一个变革性的概念，即绿色网络基础设施（CI）。请记住，IT行业消耗的能源与航空业一样多（碳足迹相同），该项目使来自宏基因组学、海洋观测、显微镜、生物信息学和数字媒体的五个应用科学家社区能够了解如何测量并最大限度地减少能源消耗，利用新型能源/冷却源，并采用中间件来自动化计算/电源策略的最佳选择。解决的研究问题包括研究应用程序到虚拟机的动态迁移以降低功耗，研究虚拟机到物理机的迁移以实现网络局部性，开发新的电源/热管理策略（闭环，使用传感器的反馈），在gpu和fpga等协同处理硬件的背景下分类科学算法，开发异构平台上的资源共享/调度算法。全尺寸虚拟化设备“绿光仪器”（GreenLight Instrument）将用于测量、监控和公开（通过面向服务的体系结构方法）实时传感器输出，使任何地方的研究人员都能研究大规模科学计算的能源成本。因此，这项工作使领域应用研究人员能够继续利用硅技术的指数级改进，并在全球范围内竞争。尽管IT行业已经开始制定“绿化”战略。传统的数据中心，现代校园CI的物理现实目前涉及部门设施中临时和次优能源环境的复杂网络。由于计算和数据密集型研究方法的价值，这些设施的数量增加得非常快，造成了校园范围内的空间、电力和冷却危机。这个项目解决了这些重要的问题，提供了改进的可能性。更广泛的影响：该项目使研究人员能够对节能网络基础设施（CI）进行定量探索，并培养下一代具有能源意识的科学家。它招收了来自五个学科项目的研究生，涉及少数民族服务机构，并可能对国家的商业组成部分产生直接影响。CI。

Proposal #: CNS 08-21155PI(s): DeFanti, Thomas A. Krueger, Ingolf H.; Papadopoulos, Philip M.; Smarr, Larry L.; Vahdat, Amin M.Institution: University of California ? San Diego La Jolla, CA 92093-0934Title: MRI/Dev.: Development of Instrumentation for Project Green LightProject Proposed: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.Broader Impacts: The project enables researchers to carry-out quantitative explorations into energy efficient CyberInfrastructure (CI) and to train the next generation of energy-aware scientists. It enlists graduate students from five disciplinary projects, involves minority serving institutions, and is likely to have direct impact on commercial components of the nation?s CI.