ITR: The OptIPuter

OptIPuter项目探索了一种新的分布式信息基础设施的体系结构(NSF将其称为信息结构)，这是本十年的许多科学和工程共享设施所需要的。该项目是由NSF的EarthScope和NIH的生物医学成像研究网络(BIRN)这两个社区系统的领导者密切合作推动的，这两个系统都开始产生加速的数据洪流，这些数据将存储在分布式联合数据存储库中。阻碍这类科学的一个特征是，与当今网络上可以交互操作或可视化的数据对象相比，单个数据对象(3D大脑图像或地形数据集)很大(GB)。这些科学家需要的是连接PC集群、存储和可视化系统的超高速、可预测的“畅通通道”网络，使合作的科学家能够交互地探索以前不相关的海量数据。在接下来的几年里，有一个重要的机会为这一所需的科学信息结构开发一个激进的新架构。观察到带宽和存储的指数增长率现在远远高于摩尔定律，这项研究“走到了彩虹的尽头”，探索了一个中心架构元素是光网络而不是计算机的新世界。这种转变是由并行性的使用引起的，就像十年前的超级计算一样。然而，这一次的并行是在单根光纤上的多个波长的光，或称波长，创造了超级网络。OptIPuter项目旨在重新优化整个网格软件抽象堆栈，学习如何像George Gilder建议的那样，在这个价值倒置的新世界中“浪费”带宽和存储空间，以节省“稀缺”的计算。在这样一个技术范式转变的时期，需要大规模的应用驱动系统实验和广泛的多学科团队，以理解和开发针对“LambdaGrid”世界的创新解决方案。规模较小的努力不太可能产生抓住机遇所需的根本性变化。如果不处理这个研究领域，发展电子科学信息结构的更传统的方法将被广泛采用，但从长远来看，我们失去科学领导地位会给国家带来什么最终代价？我们的方法并不是没有风险；然而，随着这些指数交叉，因此不可避免地对信息结构体系结构考虑进行技术驱动的重新排序，现在使一个令人兴奋的研究机会成为可能。从本质上讲，OptIPuter是一台“虚拟”并行计算机，其中的各个“处理器”是分布广泛的集群；“底板”由IP提供，通过多个专用的Lambdas(每个1-10 Gbps)提供；而“海量存储系统”是大型分布式科学数据储存库，由科学仪器作为OptIPuter的外围设备，近乎实时地运行。此外，协作将是OptIPuter的一个决定性特征；目标包括实施具有光纤多播的下一代接入网格，实现与现实匹配的可视分辨率的平铺立体声HDTV屏幕。OptIPuter是埃里希·施密特在20世纪90年代中期预言的“计算机空心化”愿景的体现。旧的“盒子里的电脑”正在被炸毁，并散布在网络上。OptIPuter的基本发明包括软件和中间件抽象，以在波长丰富的世界中提供独特的功能，在这个世界中，终端交付的带宽大于单个计算机可以饱和的带宽。这项针对校园和大城市规模的OptIPuters研究是对州(加利福尼亚州的CENIC/ONI、伊利诺伊州的I-Wire)、国家(TeraGrid)和国际(Starlight)项目的补充。由六所大学组成的OptIPuter研究团队涵盖了应用程序、软件、网络和硬件专业知识，以应对挑战。这个团队在成功管理大型多学科和多机构项目、与公司合作以及提供硬件和软件系统方面的高影响力创新方面有着悠久的历史。由于行业正在开发OptIPuter的关键子组件，几家领先的公司作为合作伙伴参与其中。新的体系结构模型和使其发挥作用的软件系统应该为其他联邦资助的大型网络科学设施做出重要贡献。除了研究之外，与远程仪器相结合的协作可视化数据融合OptIPuter中心将使技术能够满足更广泛的社会需求，包括应急响应、国土安全、医疗服务和科学教育。

The OptIPuter project explores a new architecture for the distributed information infrastructure (which NSF terms infostructure) required by a number of this decade's science and engineering shared facilities. The project is driven by a close collaboration with leaders of two of these community systems?NSF's EarthScope and NIH's Biomedical Imaging Research Network (BIRN)?both of which are beginning to produce an accelerating flood of data which will in stored in distributed federated data repositories. One characteristic blocking such science is that the individual data objects (a 3D brain image or a terrain dataset) are large (Gigabytes) compared to what can be interactively manipulated or visualized over today's networks. What these scientists require are ultra-high-speed predictable "clear-channel" networks linking PC clusters, storage and visualization systems, enabling collaborating scientists to explore interactively massive amounts of previously uncorrelated data. An important opportunity exists over the next few years to develop a radical new architecture for this needed scientific infostructure. Observing that the exponential growth rates in bandwidth and storage are now much higher than Moore's Law, this research "goes to the end of the rainbow" to exploit a new world in which the central architectural element is optical networking, not computers. This transition is caused by the use of parallelism, as in supercomputing a decade ago. However, this time the parallelism is in multiple wavelengths of light, or lambdas, on single optical fibers, creating supernetworks. The OptIPuter project aims at the re-optimization of the entire Grid stack of software abstractions, learning how, as George Gilder suggests, to "waste" bandwidth and storage in order to conserve "scarce" computing in this new world of inverted values. Such a period of technological paradigm shifting requires large-scale application-driven system experiments and a broad multidisciplinary team to understand and develop innovative solutions for a "LambdaGrid" world. Smaller scale efforts are unlikely to produce the radical changes needed to seize the opportunity. Without tackling this research arena, more traditional approaches to developing e-Science infostructure will instead be widely adopted, but at what ultimate cost to the country in our loss of scientific leadership in the long term? Our approach is not without risk; however, with these exponentials crossing, and therefore a technologically driven reordering of infostructure architectural considerations inevitable, an exciting research opportunity is now made possible. Essentially, the OptIPuter is a "virtual" parallel computer in which the individual "processors" are widely distributed clusters; the "backplane" is provided by IP delivered over multiple dedicated lambdas (each 1-10 Gbps); and, the "mass storage systems" are large distributed scientific data repositories, fed by scientific instruments as OptIPuter peripheral devices, operated in near real-time. Furthermore, collaboration will be a defining OptIPuter characteristic; goals include implementing a next-generation Access Grid with optical multicast, enabling tiled stereo HDTV screens of reality-matching visual resolution. The OptIPuter is an embodiment of the vision of the "hollowing out of the computer" prophesized by Erich Schmidt in the mid-1990s. The old "computer-in-a-box" is being blown up and scattered across the Net. The OptIPuter's fundamental inventions include software and middleware abstractions to deliver unique capabilities in a lambda-rich world, a world in which endpoint-delivered bandwidth is greater than individual computers can saturate. This research on campus and metro-scale OptIPuters complements State (CENIC/ONI in California, I-WIRE in Illinois), national (TeraGrid), and international (StarLight) projects. The six-university OptIPuter research team spans applications, software, networking and hardware expertise to address the challenges. This team has a long history of successfully managing large multidisciplinary and multi-institutional projects, working with companies, and delivering high-impact innovations in hardware and software systems. Since industry is developing key subcomponents of the OptIPuter, several leading companies are involved as partners. The new architectural models and the software systems to make them function should contribute important capabilities to other large-scale Federally funded networked science facilities. Going beyond research, the collaborative visualization data-fusion OptIPuter centers coupled to remote instrumentation will be enabling technologies for broader societal needs, including emergency response, homeland security, health services, and science education.