Learn · Computational Methods in Materials Science and Engineering
Lecture 3 of 34Week 1
From core Python to NumPy to C: Matrix Multiplication and Performance
Prof. Saswata Bhattacharya and Prof. Anuj Goyal · IIT Hyderabad
Credits and licence
- From
- Computational Methods in Materials Science and Engineering, IIT Hyderabad (at NPTEL)
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only.
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge. Coordinated by IIT Madras.
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All the lectures
- Programming Foundations for Computational Methods.
- Python Programming Practice Workbook
- From core Python to NumPy to C: Matrix Multiplication and Performance
- Systems of Linear Equations
- Direct Methods to Solve Systems of Linear Equations - Part 1
- Direct Methods to Solve Systems of Linear Equations - Part 2
- Linear systems Iterative Methods Part 1
- Root fonding
- Solving systems of Non linear Equations
- Numerical Interpolation and Differentiation Part 1
- Numerical Interpolation and Differentiation Part 2
- Numerical Integration
- Implementation of Numerical Interpolation, Least Squares, Differentiation Part 1
- Implementation of Numerical Interpolation, Least Squares, Differentiation Part 2
- Gaussian Quadrature - Theory and Implementation
- Implementation of Numerical Integration
- Understanding Least Squares Part 1
- Understanding Least Squares Part 2
- Introduction to Ordinary and Partial Differential Equations - Part 1
- Numerical Methods to Solve ODEs - Initial Value Problems - Part 1
- Numerical Methods to Solve ODEs - Initial Value Problems - Part 1B
- Implementation of Numerical Methods to Solve ODEs - Initial Value Problems
- Introduction to the Monte Carlo Method for integration
- Solving Systems of Ordinary Differential Equations
- Matrix Eigenvalue Problems
- Introduction to Optimization Part 1
- Inroduction to Optimization Part 2
- Introduction to Numerical Methods to Solve Boundary Value Problems
- Optimization Part 3: Steepest Descent Technique
- Introduction to Partial differential equations
- Optimization Part 4
- Numerical methods to solve partial differential equations -1
- Parabolic PDEs Part 1: Heat Equation and FTCS Method
- Parabolic PDEs Part 2: Von Neumann Stability Analysis