In this paper, we present GaccO-a main memory DBMS for GPU-accelerated OLTP. For executing OLTP workloads, GaccO implements a novel scheme that splits the execution across the CPU and the GPU. Using such a co-execution scheme GaccO can thus not only efficiently make use of the vectorized execution of the GPU by grouping transactions of the same type into batches, but it can also support databases larger than device memory by leveraging CPU memory in addition to the GPU memory. In our evaluation with TPC-C, we show that GaccO can thus speed-up OLTP workloads by up to 6 times compared to a pure CPU-based OLTP execution.
CITATION STYLE
Boeschen, N., & Binnig, C. (2022). GaccO-A GPU-accelerated OLTP DBMS. In Proceedings of the ACM SIGMOD International Conference on Management of Data (pp. 1003–1016). Association for Computing Machinery. https://doi.org/10.1145/3514221.3517876
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