Existing work on accelerating analytic DB query processing with (discrete) GPUs fails to fully realize their potential for speedup through parallelism: Published results do not achieve significant speedup over more performant CPU-only DBMSes when processing complete queries. This paper presents a successful e

Additional Metadata
Stakeholder Intel, GE Global Rsearch
Persistent URL dx.doi.org/10.1007/978-3-319-56111-0_4
Series Lecture Notes in Computer Science
Conference International Workshop on Accelerating Data Management Systems Using Modern Processor and Storage Architectures
Citation
Agbaria, A, Minor, D, Peterfreund, N, Rozenberg, E, Rosenberg, O, & Huawei Research. (2016). Overtaking CPU DBMSes with a GPU in whole-query analytic processing with parallelism-friendly execution plan optimization. In Proceedings of the International Workshop on Accelerating Analytics and Data Management Systems Using Modern Processor and Storage Architectures (pp. 57–78). doi:10.1007/978-3-319-56111-0_4