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teaching:mfe:is [2019/05/13 12:39] mahmsakr |
teaching:mfe:is [2019/06/07 14:56] svsummer [Dynamic Query Processing on GPU Accelerators] |
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| - | ===== Dynamic Query Processing on GPU Accelerators ===== | ||
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| - | This master thesis is put forward in the context of the DFAQ Research Project: "Dyanmic Processing of Frequently Asked Queries", funded by the Wiener-Anspach foundation. | ||
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| - | Within this project, our lab is hence developing novel ways for processing "fast Big Data", i.e., processing of analytical queries where the underlying data is constantly being updated. The analytics problems envisioned cover wide areas of computer science and include database aggregate queries, probabilistic inference, matrix chain computation, and building statistical models. | ||
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| - | The objective of this master thesis is to build upon the novel dynamic processing algorithms being developed in the lab, and complement these algorithms by proposing dynamic evaluation algorithms that execute on modern GPU architectures, thereby exploiting their massive parallel processing capabilities. | ||
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| - | Since our current development is done in the Scala programming language, prospective students should either know Scala, or being willing to learn it within the context of the master thesis. | ||
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| - | **Validation of the approach** Validation of master thesis' work should be done on two levels: | ||
| - | * a theoretical level; by proposing and discussing alternative ways to do incremental computation on GPU architectures, and comparing these from a theoretical complexity viewpoint | ||
| - | * an experimental level; by proposing a benchmark collection of CEP queries that can be used to test the obtained versions of the interpreter/compiler, and report on the experimentally observed performance on this benchmark. | ||
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| - | **Deliverables** of the master thesis project | ||
| - | * An overview of query processing on GPUs | ||
| - | * A definition of the analytics queries under consideration | ||
| - | * A description of different possible dynamic evaluation algorithms for the analytical queries on GPU architectures. | ||
| - | * A theoretical comparison of these possibilities | ||
| - | * The implementaiton of the evaluation algorithm(s) (as an interpreter/compiler) | ||
| - | * A benchmark set of queries and associated data sets for the experimental validation | ||
| - | * An experimental validation of the compiler, and analysis of the results. | ||
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| - | **Interested?** Contact : [[svsummer@ulb.ac.be|Stijn Vansummeren]] | ||
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| - | **Status**: available | ||
| ===== Multi-query Optimization in Spark ===== | ===== Multi-query Optimization in Spark ===== | ||