Graduation Year


Document Type




Degree Granting Department

Computer Engineering

Major Professor

N.Ranganathan, Ph.D.

Committee Member

Murali Varanasi, Ph.D.

Committee Member

Abdel Ejnoui, Ph.D.


High-Level Synthesis, Resource Optimization, Low Power Binding, CDFG Extraction, Tabu Search, Game Theory


In this thesis, a new tool, named CHESS, is designed and developed for control and data-flow graph (CDFG) extraction and the high-level synthesis of VLSI systems. The tool consists of three individual modules for:(i) CDFG extraction, (ii) scheduling and allocation of the CDFG, and (iii) binding, which are integrated to form a comprehensive high-level synthesis system. The first module for CDFG extraction includes a new algorithm in which certain compiler-level transformations are applied first, followed by a series of behavioral-preserving transformations on the given VHDL description. Experimental results indicate that the proposed conversion tool is quite accurate and fast. The CDFG is fed to the second module which schedules it for resource optimization under a given set of time constraints. The scheduling algorithm is an improvement over the Tabu Search based algorithm described in [6] in terms of execution time. The improvement is achieved by moving the step of identifying mutually exclusive operations to the CDFG extraction phase, which, otherwise, is normally done during scheduling. The last module of the proposed tool implements a new binding algorithm based on a game-theoretic approach. The problem of binding is formulated as a non-cooperative finite game, for which a Nash-Equilibrium function is applied to achieve a power-optimized binding solution. Experimental results for several high-level synthesis benchmarks are presented which establish the efficacy of the proposed synthesis tool.