ITR: Parallel and Grid Computing for Ecological Multimodeling

University Of Tennessee Knoxville, Knoxville TN

Investigators

Abstract

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.