This course introduces the theory of parallel and VLSI computation such as models of parallel computation, parallel algorithms and architectures, area-time complexity for VLSI, and quantum computation.
At the end of this course, students will be able to:
1) Explain models and computational complexity of parallel computation.
2) design and analize parallel algorithms.
3) explain the principle of quantum computation.
model of parallel computation, parallel algorithm, computational complexity, VLSI, Boolean circuit, reversible circuit, quantum circuit
✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | Practical and/or problem-solving skills |
Students should review the topics covered in each class.
Course schedule | Required learning | |
---|---|---|
Class 1 | Introduction | Students must make sure they understand what significance the course holds for them by chechking their learning portfolio. |
Class 2 | RAM Computation | Review of serial algorithms and computational complexity |
Class 3 | PRAM model | Understand the PRAM model of parallel computation |
Class 4 | Sorting on PRAM | Analysis of parallel sorting algorithms on PRAMs |
Class 5 | Parallel Computational Complexity | Understand the complexity of parallel computation |
Class 6 | Network Model | Understand the network model of parallel computation |
Class 7 | Sorting on Arrays | Analysis of parallel sorting algorithms on arrays |
Class 8 | Parallel Computation on Hypercubes | Analysis of parallel sorting algorithms on hypercubes |
Class 9 | VLSI Layout | Understand the VLSI layouts |
Class 10 | VLSI Computational Complexity | Understand the area-time complexity of VLSI |
Class 11 | Boolean Circuit Complexity | Understand the complexity of Boolean circuits |
Class 12 | Physics of Computation | Understand physics of computation |
Class 13 | Reversible Circuits | Understand reversible circuits |
Class 14 | Quantum Circuits | Understand quantum circuits |
Class 15 | Quantum Computation | Analysis of quantum algorithms |
None required.
Course materials are provided during class.
Students' course scores are based on their reports.
No prerequisites are necessary, but enrollment in the course of discrete structures and algorithms or equivalent is desirable.