XPS: DSD: A2MA - Algorithms and Architectures for Multiresolution Applications

这项研究项目的目标是设计新的方法和设备来解决计算科学和工程中需要高强度算术运算(也称为每秒浮点运算，或“FLOPS”)的问题。在这种计算密集型技术的研究和开发中面临的许多障碍之一是实现对现有计算资源的能效利用。与汽车设计中使用的里程/加仑度量类似，人们对一种可用于新计算技术设计的度量感兴趣：优化FLOPS/瓦特。这项研究将致力于设计新的算法和架构来优化这一指标。这些算法和体系结构将针对一类特定的科学计算问题而定制：基于树的有限元方法和N体问题。有可能设计出并行良好且能量高效的算法(即，产生高的“峰值百分比”测量)。然而，通常情况下，这样的算法会牺牲工作的最优性。在实现工作最优化和能源效率的同时，设计这样做的算法要困难得多。节点利用率墙-这是90年代初以来的一个长期问题-不仅没有得到解决，而且随着更深层次的内存层次结构和许多核心和异类体系结构的出现而变得更加尖锐。与此同时，不仅使算法适应体系结构的变化，而且从算法需求驱动体系结构设计，还有巨大的未开发潜力。这项研究将确定基于树的算法的设计空间(在工作最优和最大并发的约束下)，评估最新代码的性能，并探索定制的算法/硬件平台。预计这一项目将产生一些更广泛的影响。目标方法论在地球科学、工程学、宇宙学、生物学和数据分析中得到应用。除了研究活动，还将设计一个教育和传播计划，向学生和研究人员以及更广泛的计算和应用科学家受众传达这项工作的结果。

The goal of this research project is to devise novel methodologies anddevices for problems in computational science and engineering thatrequire high-intensity of arithmetic operations (also known asFloating-point Operations Per Second, or ``FLOPS''). Among the manyhurdles faced in research and development of such compute-intensivetechnologies is achieving energy-efficient utilization of theavailable computing resources. Similar to the miles/gallon metric usedin automotive design, one is interested in a metric that can be usedin the design of new computing technologies: optimizingFLOPS/watt. This research will be on designing novel algorithms andarchitectures that optimize this metric. These algorithms andarchitectures will be customized to a particular class of scientificcomputing problems: tree-based finite element methods and N-bodyproblems.It is possible to devise algorithms that parallelize well and are energy efficient (i.e., produce high ``percentage-of-peak''measurements). Often, however, such algorithms sacrifice workoptimality. It is much more difficult to design algorithms that do sowhile achieving both work optimality and energy efficiency. Thison-node utilization wall---a chronic problem since the earlynineties---not only remains unresolved but has become more acute withthe emergence of deeper memory hierarchies and manycore andheterogeneous architectures. At the same time, there is a largeuntapped potential by not only adapting algorithms to architecturalchanges, but instead driving architecture design from algorithmrequirements. This research will identify the design space fortree-based algorithms (under the constraints of work-optimality andmaximum concurrency), evaluate performance of state-of-the-art codes,and explore custom algorithm/hardware platforms. A number of broaderimpacts are anticipated from this project. The target methodologiesfind applications in earth sciences, engineering, cosmology, biology,and data analysis. Along with the research activities, an educationaland dissemination program will be designed to communicate the resultsof this work to both students and researchers, as well as a moregeneral audience of computational and application scientists.