Collaborative:Balanced Scalable Architectures for Data-Intensive Supercomputing

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。科学计算的本质正在发生变化：它越来越以数据为中心。我们使用Amdahl定律来量化(i)什么是数据密集型计算问题，以及（ii）什么是数据密集型计算架构。基于这些客观指标，我们提出了几种不同的架构方法，包括一些下一代低功耗处理器和存储设备，例如固态硬盘（ssd），并考虑这些架构如何提供实质性的好处。在这项研究中，我们计划探索在数据库服务器的背板上执行科学数据处理的第一步的方法，这是我们最接近低级科学数据的方法。我们还将探讨如何在关系数据库和类似MapReduce/Hadoop的环境中使用树和数组来表示非常大的科学数据集。虽然ssd可以为顺序和随机I/ o提供出色的性能，但我们仍然需要传统硬盘来处理大容量卷。这项研究将重新思考和重新设计我们现有的数据库集群和数据管理系统，因为这些新设备的出现无疑为提高性能和能源效率带来了令人兴奋的机会。该提案中的教育和推广计划包括四项任务：开发教育材料，指导代表性不足的学生，发展行业合作和公共推广活动。我们计划将它们穿插在一起，以最大限度地扩大在多个方面的影响。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). The nature of scientific computing is changing: it is becoming increasingly data-centric. We use Amdahl's Laws to quantify (i) what is a data-intensive computational problem, and (ii) what is a data-intensive computational architecture. Based on these objective metrics we propose several different architectural approaches, including some next-generation, low-power processors and storage devices, e.g., Solid-State Drives (SSDs), and consider how these architectures might provide substantial benefits. In this research, we plan to explore approaches where the first steps of the scientific data processing are performed on the backplane of the database servers, the closest we can get to low level scientific data. We will also explore how we can use trees and arrays, representing very large scientific data sets, in both relational databases and on a MapReduce/Hadoop like environment. While SSDs can provide an excellent performance for both sequential and random I/Os, we will still need traditional hard disks for the bulk volume. This research will rethink and redesign our existing database clusters and data management systems, as the emergence of these new devices has undoubtedly introduced exciting opportunities for improving not only performance but also energy efficiency. The education and outreach plan in this proposal consists of four tasks: developing educational materials, mentoring underrepresented students, developing collaborations in the industry and public outreach activities. We plan to interleave them to maximize the broader impact on multiple fronts.