A case study in preserving a high energy physics application with Parrot

21st International Conference on Computing in High Energy and Nuclear Physics

物理学;计算机科学

Meng, H.^1 ; Wolf, M.^2 ; Ivie, P.^1 ; Woodard, A.^2 ; Hildreth, M.^2 ; Thain, D.^1

Department of Computer Science and Engineering, University of Notre Dame, Notre Dame

IN

46556, United States^1

Department of Physics, University of Notre Dame, Notre Dame

IN

46556, United States^2

关键词: Amazon ec2;    Cloud platforms;    Fine grained;    Networked resources;    Reproducibilities;    Scientific results;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/664/3/032022/pdf
DOI  :  10.1088/1742-6596/664/3/032022

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

The reproducibility of scientific results increasingly depends upon the preservation of computational artifacts. Although preserving a computation to be used later sounds easy, it is surprisingly difficult due to the complexity of existing software and systems. Implicit dependencies, networked resources, and shifting compatibility all conspire to break applications that appear to work well. To investigate these issues, we present a case study of a complex high energy physics application. We analyze the application and attempt several methods at extracting its dependencies for the purposes of preservation. We propose one fine-grained dependency management toolkit to preserve the application and demonstrate its correctness in three different environments - the original machine, one virtual machine from the Notre Dame Cloud Platform and one virtual machine from the Amazon EC2 Platform. We report on the completeness, performance, and efficiency of each technique, and offer some guidance for future work in application preservation.