Abstract: Database is a key workload in data analysis, artificial intelligence, cloud computing, big data, and other fields, and it is the key to improving the overall performance of the system. The query execution efficiency of traditional database systems is low, and the CPU usually needs to process tran- saction loads first, so that data query becomes a bottleneck that restricts the performance and efficiency of the entire system. In order to improve the systems ability of supporting large-scale data and high- intensity instantaneous concurrent access, a CPU+FPGA heterogeneous architecture is proposed to accelerate database queries. The accelerator is integrated into the CPU by using coherent acceleration processor interfaces. The way of customizing multi-engine configurable query logic in FPGA accelerates database query. The commonly used SQL query statement SELECT is focused on, and the advantages of the system in terms of latency and simplified software stack are analyzed in detail. Finally, the Inspur F37X acceleration card and Inspur server were used to verify the function and performance of the acceleration model. The test results show that, compared with the latest CPU-based query method, the proposal increase the overall processing speed by 3 to 9 times. The accelerated structure of structural computing can be applied in the design of database hardware specialization in the future.

Key words: database query, heterogeneous acceleration, heterogeneous architecture, coherent accele- ration processor interface, Postgre SQL