Publication | Closed Access
SABER
124
Citations
44
References
2016
Year
Unknown Venue
Cluster ComputingHeterogeneous ComputingEngineeringComputer ArchitectureModern ServersData Streaming ArchitectureData ScienceData IntegrationParallel ComputingData ManagementStream ProcessingHeterogeneous ArchitectureSql QueriesStreaming EngineComputer EngineeringComputer ScienceData Stream ManagementCloud ComputingParallel Programming
Modern servers have become heterogeneous, often combining multi-core CPUs with many-core GPGPUs. Such heterogeneous architectures have the potential to improve the performance of data-intensive stream processing applications, but they are not supported by current relational stream processing engines. For an engine to exploit a heterogeneous architecture, it must execute streaming SQL queries with sufficient data-parallelism to fully utilise all available heterogeneous processors, and decide how to use each in the most effective way. It must do this while respecting the semantics of streaming SQL queries, in particular with regard to window handling.
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