Hybrid^2-Index Structures for Main Memory Databases

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The goal of the project is to speed up index accesses of database management systems (DBMS) in order to improve the total performance. As index accesses are starting points for all succeeding processing steps of database queries, fast index accesses are the key to a superior total performance of DBMS. For the purpose of speeding up index accesses we propose to investigate and develop new hardware-/software index structures, which realize structure-hybrid indexes, i.e., the combination of static and dynamic indexes, on hybrid shared-memory system architectures consisting of a CPU and an FPGA or GPU as hardware accelerator. Such hybrid^2-indexes are not considered so far in literature, such that the possibilities of current hybrid shared-memory system architectures are not utilized in an optimal way. Because of the reduction of the communication costs between CPU and hardware accelerator many existing design rules for utilizing hardware accelerators must be rethought, especially concerning the complexities of tasks taken over by the hardware accelerators.Within this project we will hence research on which and how static and dynamic index structures can be realized in an efficient way with high performance on hybrid systems. Furthermore, we will investigate how to react on changing access patterns by dynamically swapping used index structures on the hardware accelerators. We expect novel, adaptive structure- and hardware-hybrid index structures, which significantly improve the performance of index accesses in DBMS in comparison to existing traditional systems.