Abstract
The paper addresses practical challenges related to the development and application of distributed software packages of the Orlando Tools framework to solve real problems. Such packages include a special class of scientific applications characterized by a wide class of problem solvers, modular structure of software, algorithmic knowledge implemented by modules, computations scalability, execution in heterogeneous resources, etc. It is adapted for various categories of users: developers, administrators, and end-users. Unlike other tools for developing scientific applications, Orlando Tools provides supports for the intensive evolution of algorithmic knowledge, adaptation of existed and designing new ones. It has the capability to extend the class of solved problems. We implement and automate the non-trivial technological sequence of the collaborative development and use of packages including the continuous integration, delivery, deployment, and execution of package modules in a heterogeneous distributed environment that integrates grid and cloud computing. This approach reduces the complexity of the collaborative development and use of packages, and increases software operation predictability through the preliminary detecting and eliminating errors with significant reduction of the correcting cost.
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Acknowledgment
The study is supported by the Russian Foundation of Basic Research, projects no. 19-07-00097-a and no. 18-07-01224-a. This work was also supported in part by Basic Research Program of SB RAS, projects no. IV.38.1.1 and no. III.17.5.1.
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Feoktistov, A., Gorsky, S., Sidorov, I., Bychkov, I., Tchernykh, A., Edelev, A. (2020). Collaborative Development and Use of Scientific Applications in Orlando Tools: Integration, Delivery, and Deployment. In: Crespo-Mariño, J., Meneses-Rojas, E. (eds) High Performance Computing. CARLA 2019. Communications in Computer and Information Science, vol 1087. Springer, Cham. https://doi.org/10.1007/978-3-030-41005-6_2
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