| Title | High-Throughput Parallel SRAM-Based Hash Join Architecture on FPGA |
| Authors | Zhao, Zhengen Li, Yuzhe Yang, Ying Li, Linlin Xu, Yunsong Zhou, Jing |
| Affiliation | Nanjing Univ Aeronaut & Astronaut, Coll Automat Engn, Nanjing 210016, Peoples R China Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Peoples R China Peking Univ, Dept Mech & Engn Sci, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China Beijing Inst Astronaut Syst Engn, Beijing 100076, Peoples R China Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB T6G 2C6, Canada |
| Keywords | CYBER-PHYSICAL SYSTEMS STATE ESTIMATION ATTACK |
| Issue Date | Nov-2020 |
| Publisher | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS |
| Abstract | The hash join operator is one of the most important relational operations used in database. The offloading and acceleration of this operation on hardware has been a technique of growing interest for a long time. However, the non-uniform distribution of data caused by hash collisions negatively affects the throughput of the hash join algorithm, owing the variation in the number of hash table accesses required for each lookup. To resolve this issue, a non-collision parallel static random-access memory (SRAM)-based hash join architecture is presented. This architecture utilizes multiple hash functions and content addressable memories (CAMs) to eliminate hash collision, thereby ensuring a worst constant memory access for each phase in the hash join algorithm and consequently improving the hash join throughput. The proposed architecture was implemented on a Xilinx field programmable gate array (FPGA), and the experimental results show that our design achieved a high hash join throughput of 153.6 million tuples per second, and a speedup factor of at least 2.5 with the best existing FPGA-based hash join architecture and a match rate of 50. |
| URI | http://hdl.handle.net/20.500.11897/599230 |
| ISSN | 1549-7747 |
| DOI | 10.1109/TCSII.2019.2953238 |
| Indexed | SCI(E) |
| Appears in Collections: | 工学院 湍流与复杂系统国家重点实验室 |
