B.E. Electronics & Comm. Engg:VLSI CADThapar University
Price on request
First Year: Semester I
First year: Semester II
Electrical and Electronic Science
Second year: Semester I
Numerical and Statistical Methods
Measurement Science and Techniques
Signals and Systems
Digital Electronic Circuits
Human Values, Ethics and IPR
Second year: Semester II
Analog Electronic Circuits
Networks and Transmission Lines
Electrical Engineering Materials
Analog Communication Systems
Data Structure and Information Technology
Third year: Semester I
Digital Signal Processing for Communications
VLSI Circuit Design
Digital Communication Systems
Linear Integrated Circuits and Applications
Summer Training(6 weeks)
Third year: Semester II
Industrial Training(6 weeks)
Fourth year: Semester I
Antenna and Wave Propagation
Modern Control Engineering
Wireless and Mobile Communication Systems
Fourth year: Semester II
Optical Communication Systems
Advanced Communication Systems
HDL Based Digital Design
Total Quality Management
Complexity of VLSI chips and trends in IC industry, VLSI design cycle, VLSI Design Flow, Y-Chart: Design abstractions using Behavioral, Structural and Physical domains, role of CAD tools in VLSI Design Automation.
Common algorithmic approaches used in VLSI Design Automation, Greedy methods, Stochastic search, Graph theoritic methods, Dynamic Programming; Optimization Algorithms: Simulated Annealing, Genetic Algorithm and Neural models.
VLSI Physical Design Automation: Algorithms for Partitioning, Floor planning, Placement Routing: Grid Routing, Channel Routing, Global routing, Layout compaction and verification, DRC checks.
Design Verification using Logic Simulation: Compiled code and Event- driven simulation Algorithms, Silicon Compilers
VLSI Design Styles: Standard IC, ASICs
Recent topics in VLSI CAD: Reconfigurable Computing, Embedded System concepts, Hardware Software Co-design, High-Level Synthesis and VHDL modeling.
Laboratory work: Working with layout editor, Implementation of Algorithms used for VLSI Design, logic simulation algorithms, Optimization algorithms- greedy methods, simulated annealing, genetic algorithm and neural models.