ITR: Parallel and Grid Computing for Ecological Multimodeling

跨越区域地理范围的环境问题要求在各种空间、时间和组织尺度上采用多种方法来模拟自然系统的响应。分析自然系统对不同人类行为的反应需要几个物理和营养尺度的数学和计算机模型。计算机建模工作需要大量的时空数据集，这些数据集通常来自遥感，与降雨和水文学等非生物因素的复杂模型相联系。由于与这些模型相关的大量空间数据集和繁重的计算需求，在工作站平台上的串行计算方法几乎不适合分析。研究人员将为链接的生态和物理模型开发算法和软件，这些模型既适用于多处理器计算机，也适用于计算网格中的机器集群。这项拟议的研究对自然系统管理者有效利用目前正在收集和存档的大量遥感数据、将这些数据与自然系统的现实生态和物理模型联系起来以及对管理情景的有效性进行评估的能力具有潜在的非常广泛的影响。考虑到替代收割、水调度和土地利用设计的成本和潜在的长期影响，重要的是优化决策并监测所采取行动的有效性。然而，要实现有效利用，还需要培养一支能够利用新技术的管理人员队伍。调查人员将开始开发教育材料，环境科学家可以通过这些材料了解如何使用多模型来解决区域环境问题。一个目标是制定一个明确的教育计划，使计算网格方法被接受为用于自然系统管理的区域规划工具包的一部分。

Environmental problems that span regional geographic extent require multiple approaches to the modelling of natural system responses at various spatial, temporal and organismal scales. Analyzing responses of natural systems to alternative human actions requires mathematical and computer models for several physical and trophic scales. Computer modeling efforts require large spatio-temporal data sets, often derived from remote sensing, linked to complex models for abiotic factors such as rainfall and hydrology. Due to the large spatial data sets and heavy computational demands associated with such models, serial computing methods on workstation platforms are barely appropriate for analysis. The investigators will develop algorithms and software for linked ecological and physical models appropriate for both multiple-processor computers and clusters of machines across a computational grid. Included will be a comparison of the performance of alternative methods and algorithms for parallelization of ecological multimodels on a variety of platforms.The proposed research has potentially very broad impacts on the ability of managers of natural systems to effectively utilize the extensive remote sensing data currently being collected and archived, link these data with realistic ecological and physical models of natural systems, and provide assessments of the effectiveness of management scenarios. Given the costs and potential long-term impacts of alternative harvesting, water scheduling, and land-use designs, it is important to optimize decision making and monitor the effectiveness of the actions taken. Achieving effective use, however, also requires the development of a cadre of managers able to make use of new technologies. The investigators will initiate the development of educational materials through which environmental scientists can learn about the use of multimodels to address regional environmental problems. An objective is to formulate an explicit educational program that will lead to computational grid methods being accepted as part of the toolkit applied in regional planning for management of natural systems.