"The Yin and Yang of processing data warehousing queries on GPU devices"  

Yuan Yuan, Rubao Lee, and Xiaodong Zhang

Proceedings of 39th International Conference on Very Large Data Bases
(VLDB 2013), Riva del Garda, Trento, Italy, August 26-30, 2013.


Abstract

Database community has made significant research efforts to
optimize query processing on GPUs in the past few years.
However, we can hardly find that GPUs have been truly
adopted in major warehousing production systems. Preparing
to merge GPUs to the warehousing systems, we have
identified and addressed several critical issues in a three dimensional
study of warehousing queries on GPUs by varying
query characteristics, software techniques, and GPU hardware
configurations. We also propose an analytical model
to understand and predict the query performance on GPUs.
Based on our study, we present our performance insights for
warehousing query execution on GPUs. The objective of our
work is to provide a comprehensive guidance for GPU architects,
software system designers, and database practitioners
to narrow the speed gap between the GPU kernel execution
(the fast mode) and data transfer to prepare GPU execution
(the slow mode) for high performance in processing data
warehousing queries. The GPU query engine developed in
this work is open source to the public.