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Green Simulation: A Methodology for Reusing the Output of Past Computer Simulation Experiments

绿色仿真：重用过去计算机仿真实验输出的方法

基本信息

批准号：
1634982
负责人：
Barry Nelson
金额：
$ 29.93万
依托单位：
Northwestern University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-01-01 至 2021-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1634982&HistoricalAwards=false
关键词：
Green Simulation Methodology Reusing Output

项目摘要

The standard practice in computer simulation experiments is to run an experiment to answer a question, and use the experiment's output only to answer that question. When future questions arise that are not answered adequately by output from past experiments, that output is not used at all in answering them. Instead, a new experiment is run, as though it were the first experiment run with that simulation model. This award will help make methods to make computer simulation experiments more efficient by reusing the output of old experiments. Simulation modeling is an important tool in military, business, science, and engineering applications. Computer simulation experiments often occupy scarce, expensive high-performance computing facilities and consume substantial amounts of electricity. If successful, this research will benefit society by reducing the resources consumed by computer simulation experiments. The project includes opportunities to train Ph. D. students and to integrate research findings into Ph. D. courses on simulation. Efforts will be made to recruit students from underrepresented groups; several female students have been part of the principal investigator's research group.The objective of this research is to improve the computational efficiency of stochastic simulation experiments in a setting in which there is a sequence of repeated experiments using the same simulation model with different inputs. Outputs of this research will include algorithms that have the potential to improve the efficiency of later experiments by storing and reusing the output of earlier experiments. The methods to be employed include the likelihood ratio method, metamodeling, and variance reduction techniques for stochastic simulation. This research is also applicable more broadly to statistics and analytics, not just to simulation. It will develop experimental designs that take into account the availability of data from previous experiments, determining what additional data may be acquired to answer the question at hand.

计算机模拟实验的标准做法是运行一个实验来回答一个问题，并仅使用实验的输出来回答该问题。当未来的问题出现时，过去实验的输出不能充分回答，这个输出根本不用于回答它们。相反，运行一个新的实验，就好像它是第一个使用该仿真模型运行的实验一样。该奖项将有助于通过重用旧实验的输出来提高计算机模拟实验的效率。仿真建模是军事、商业、科学和工程应用中的重要工具。计算机仿真实验通常占用稀缺、昂贵的高性能计算设施，并消耗大量的电力。如果成功，这项研究将通过减少计算机模拟实验消耗的资源而造福社会。该项目包括培养博士的机会。学生和研究成果整合到博士学位。模拟课程。主要研究者的研究小组中有几名女学生。本研究的目的是提高随机模拟实验的计算效率，在这种情况下，使用相同的模拟模型和不同的输入进行一系列重复实验。这项研究的输出将包括有可能通过存储和重用早期实验的输出来提高后期实验效率的算法。所采用的方法包括似然比方法，元建模，和方差减少随机模拟技术。这项研究也适用于更广泛的统计和分析，而不仅仅是模拟。它将开发实验设计，考虑到以前实验数据的可用性，确定可以获得哪些额外数据来回答手头的问题。