Print Email Facebook Twitter Multi-way Hash Join Based on FPGAs Title Multi-way Hash Join Based on FPGAs Author Huang, Kangli (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Hofstee, H.P. (mentor) Fang, J. (graduation committee) Degree granting institution Delft University of Technology Programme Electrical Engineering | Microelectronics Date 2018-01-30 Abstract The multi-way hash join is one of the commonly used and time-consuming database operations. Many algorithms have been developed to accelerate this operation, some of which use accelerators such as field programmable gate arrays (FPGAs). However, most of the previous work was focused on computation-intensive operations such as (de)compression, because the interface between the FPGA and the host can only provide relatively low bandwidth.\parHowever, new generation high-bandwidth, low-latency interfaces to interconnect host processors and accelerators such as the open coherent accelerator processor interface(OpenCAPI) provide FPGAs with new opportunities to accelerate database operations. In this thesis, we explore the potential of using OpenCAPI-attached FPGAs to accelerate multi-way joins. Via the OpenCAPI, the FPGA can obtain a high-bandwidth communicating with CPUs and the main memory at 25.6GB/s. We first investigate the previous research in software-based multi-way joins and observe that this operation is limited by the bandwidth of main memory. Thus, the main challenge of designing the accelerator emerges as avoiding unnecessary memory accesses. We partition the build relations into the size that can build a hash table in Block RAMs (BRAMs), and avoid multiple-pass memory accesses. In our design, the intermediate join phase is pipelined with a partition phase to reduce the size of the intermediate results. The proposed design is configurable for the attached bandwidth, and it can achieve a throughput of 5 GB/s when a 25.6 GB/s bandwidth is provided. Subject Heterogeneous accelerationFPGAsHash joinMulti-way JoinThe relational databaseTPC-HOpenCAPI To reference this document use: http://resolver.tudelft.nl/uuid:17f9df3a-df17-43f3-b92e-eeaf06a6903a Coordinates 51.998758, 4.373626 Part of collection Student theses Document type master thesis Rights © 2018 Kangli Huang Files PDF Master_Thesis_Kangli_Huang.pdf 2.03 MB Close viewer /islandora/object/uuid:17f9df3a-df17-43f3-b92e-eeaf06a6903a/datastream/OBJ/view