A Highly Parallel Fine-Grained Sort-Merge Join on Near Memory Computing

In-time processing of database system is imperative to reveal the hidden information. JOIN operation is critical in data analysis, as it occupies almost half of the average execution time in the standard TPC-H benchmark for database processing. In modern databases, transferring data between computing engines and system memory has become one of the main performance challenges. Previous works of Near Memory Computing (NMC) alleviated the costly data transfer, however, the designs still pose inefficiency in terms of processing flow and data management. In this paper, we propose FG-SMJ: a highly parallel fine-grained sort-merge join on near memory computing. The novel data layout allows us to access data from memory chips with fine-grained chip-level parallelism and exploit memory bandwidth. Compared with previous NMC designs, the proposed FG-SMJ attains 3.08x speedup.