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Access Type

Open Access Thesis

Document Type


Degree Program

Electrical & Computer Engineering

Degree Type

Master of Science in Electrical and Computer Engineering (M.S.E.C.E.)

Year Degree Awarded


Month Degree Awarded



Innovations in Field Programmable Gate Array (FPGA) manufacturing processes and architectural design have led to the development of extremely large FPGAs. There has also been a widespread adaptation of these large FPGAs in cloud infrastructures and data centers to accelerate search and machine learning applications. Two important topics related to FPGAs are addressed in this work: on-chip communication and security. On-chip communication is quickly becoming a bottleneck in to- day’s large multi-million gate FPGAs. Hard Networks-on-Chip (NoC), made of fixed silicon, have been shown to provide low power, high speed, flexible on-chip communication. An iterative algorithm for routing pre-scheduled time-division-multiplexed paths in a hybrid NoC FPGA architecture is demonstrated in this thesis work. The routing algorithm is based on the well known Pathfinder algorithm, overcomes several limitations of a previous greedy implementation and successfully routes connections

using a higher number of timeslots than greedy approaches. The new algorithm shows an average bandwidth improvement of 11% for unicast traffic and multicast traffic patterns. Regarding on-chip FPGA security, a recent study on covert channel communication in Xilinx FPGA devices has shown information leaking from long interconnect wires into immediate neighboring wires. This information leakage can be used by an attacker in a multi-tenant FPGA cloud infrastructure to non-invasively steal secret information from an unsuspecting user design. It is demonstrated that the information leakage is also present in Intel SRAM FPGAs. Information leakage in Cyclone-IV E and Stratix-V FPGA devices is quantified and characterized with varying parameters, and across different routing elements of the FPGAs.


First Advisor

Russell Tessier

Second Advisor

Daniel Holcomb

Third Advisor

Jun Yao