FPGAS and Database Engines Integration

This work focuses on the integration of an FPGA with a database engine. The purpose is to design and implement hardware-accelerated algorithms that are useful for the real-time work demands of modern databases in the world of data science and “Big Data” analysis. The work proposes an integration architecture of a commercial FPGA and an open source database. As an example of application, it is proposed the encryption and decryption of data using these services implemented in an FPGA. The algorithm used is the well-known 128-bit Advanced Encryption Standard (AES). The hardware-accelerated algorithm is used within the MySQL open-source database engine by using a UDF function in the API provided by the engine to test the algorithms implemented in hardware for processing large amounts of data. The FPGA is a commercial version of the manufacturer Xilinx.Consejo Nacional de Ciencia y Tecnologí

Decision Support Database Management System Acceleration Using Vector Processor

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