Decision Support Database Management System Acceleration Using Vector Processor

Abstract

English: This work takes a top-down approach to accelerating decision support systems (DSS) on x86-64 microprocessors using true vector ISA extensions. First, a state of art DSS database management system (DBMS) is pro led and bottlenecks are identi ed. From this, the bottlenecked functions are analysed for data-level parallelism and a discussion is given as to why the existing multimedia SIMD extensions (SSE) are not suitable for capturing this parallelism. A vector ISA is derived from what is found to be necessary in these functions; additionally, a complementary microarchitecture is proposed that draws on prior research done in vector microprocessors but is also optimised for the properties found in the pro led application. Finally, the ISA and microarchitecture are implemented and evaluated using a cycle-accurate x86-64 microarchitecture simulator.