Triton Join: Efficiently Scaling to a Large Join State on GPUs with Fast Interconnects

Clemens Lutz, Sebastian Breß, Steffen Zeuch, Tilmann Rabl, Volker Markl

Proceedings of the 2022 International Conference on Management of Data · 2022 · 19 citations · 81 references

Concepts

Abstract

Database management systems are facing growing data volumes. Previous research suggests that GPUs are well-equipped to quickly process joins and similar stateful operators, as GPUs feature high-bandwidth on-board memory. However, GPUs cannot scale joins to large data volumes due to two limiting factors: (1)~large state does not fit into the on-board memory, and (2)~spilling state to main memory is constrained by the interconnect bandwidth. Thus, CPUs are often the better choice for scalable data processing.

References

81