Parallel Algorithms
- Text: "The Design and Analysis of Parallel Algorithms"
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Author: Justin R. Smith
- Publisher: Oxford University Press
- ISBN:019-507-8810
- Web page
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Notes on computing eigenvalues of matrices
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Goals of this course
To acquaint students with:
- Applications of parallel processing,
- a "taxonomy" of parallel processing architectures:
- MIMD verses SIMD
- systolic and VLSI algorithms
- types of memory access (CREW verses CRCW)
- network architectures (hypercube, butterfly)
- Overview of parallel processing and its applications
- Models of parallel computation.
- The PRAM model and SIMD computation.
- A sorting algorithm.
- Theoretical Issues
- P-completeness and inherently sequential problems.
- Relations between PRAM models.
- Linear algebra:
- Multiplication of matrices
- Reif-Pan algorithm for matrix inversion.
- Gauss-Seidel algorithm for solving systems
of linear equations.
- Applications to the numerical
solution of partial differential equations.
- Laplace's equation
- Heat equation
- Wave equation
- Quantum Computing
- Concepts of quantum mechanics (wave-particle
duality). The Copenhagen Model.
- Multi-particle systems (quantum entanglement)
- Many worlds interpretation
- Reversible computations, quantum gates
- Algorithms.
A tutorial on quantum computing
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Justin R. Smith