Load balancing by using machine learning in CPU-GPU heterogeneous database management system
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Elakaş, Anıl (2020) Load balancing by using machine learning in CPU-GPU heterogeneous database management system. [Thesis]
Official URL: https://risc01.sabanciuniv.edu/record=b2486360 _(Table of contents)
Conventional OLTP systems are slow in performance for analytical queries. In the existing heterogeneous architecture OLAP database management systems, no system distributes work using machine learning. In this study, the DOLAP architecture, which is a high-performance column-based database management system developed for shared memory architectures, is explained. Also, job distribution algorithms based on heuristic and machine learning methods have been developed for computing hardware with different characters such as CPU and GPU on the server on which the database is running, and their performance has been analyzed
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