ITR: Parallel and Grid Computing for Ecological Multimodeling

跨越区域地理范围的环境问题需要多种方法来模拟不同空间、时间和生物尺度的自然系统响应。分析自然系统对人类活动的响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，与降雨和水文等非生物因素的复杂模型相联系。由于大型的空间数据集和沉重的计算需求与这些模型，串行计算方法在工作站平台上几乎不适合分析。 研究人员将开发适用于多处理器计算机和计算网格中机器集群的相关生态和物理模型的算法和软件。包括将在各种平台上的生态多模型并行化的替代方法和算法的性能进行比较。 在这方面，教科文组织将继续与自然系统的管理人员合作，以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，并对管理设想方案的有效性进行评估。 考虑到替代性收获、水资源调度和土地使用设计的成本和潜在长期影响，优化决策并监测所采取行动的有效性至关重要。然而，要实现有效利用，还需要培养一批能够利用新技术的管理人员。调查人员 将着手编制教育材料，环境科学家可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，将导致计算网格方法被接受为工具包的一部分，应用于区域规划管理的自然系统。

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.