| KEYWORD |
Study and development of a Big Data HW Accelerator Engine based on FPGA
Reference persons LUCA STERPONE
Research Groups DAUIN - GR-05 - ELECTRONIC CAD & RELIABILITY GROUP - CAD
Description In the framework of the Big Data area, the Extract, Load and Transform (ELT) approach is an important data processing procedure to transfer raw data from a source server to a data warehouse.
Field-programmable gate array(FPGA) with highly customized circuits are the perfect candidate to not only bring better performances but also lower power consumption to accelerate computation intensive segments for an application. The goal of the present thesis is to develop a new ELT hardware engine on Xilinx Zynq SRAM-based FPGAs interfaced with a data warehouse and to estimate the performances and the power consumption.
Required skills VHDL, C/C++, Python
Deadline 01/02/2021
PROPONI LA TUA CANDIDATURA