Abstract
This short paper proposes two novel methodologies for analyzing scientific applications in distributed environments, using workload requirements. The first explores the impact of features such as problem size and programming language, over different computational architectures. The second explores the impact of mapping virtual cluster resources on the performance of parallel applications.
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Ferro, M., Mc Evoy, G., Schulze, B. (2017). Analysis of High Performance Applications Using Workload Requirements. In: Dutra, I., Camacho, R., Barbosa, J., Marques, O. (eds) High Performance Computing for Computational Science – VECPAR 2016. VECPAR 2016. Lecture Notes in Computer Science(), vol 10150. Springer, Cham. https://doi.org/10.1007/978-3-319-61982-8_2
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DOI: https://doi.org/10.1007/978-3-319-61982-8_2
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