https://github.com/marcelo-schreiber/scientific-computing

Projects for introduction to scientific computing at UFPR
https://github.com/marcelo-schreiber/scientific-computing

c likwid scientific-computing

Last synced: 1 day ago
JSON representation

Projects for introduction to scientific computing at UFPR

• Host: GitHub
• URL: https://github.com/marcelo-schreiber/scientific-computing
• Owner: marcelo-schreiber
• Created: 2023-09-24T21:20:46.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2023-12-04T13:46:42.000Z (about 1 year ago)
• Last Synced: 2024-01-30T13:32:48.269Z (11 months ago)
• Topics: c, likwid, scientific-computing
• Homepage:
• Size: 15.6 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Scientific computing

## Other languages

- [README em português](https://github.com/marcelo-schreiber/scientific-computing/blob/master/README.pt.md)

## Introduction

This repository contains the code for the scientific computing course at the Federal University of Paraná (UFPR). The course is taught in C and covers the following topics:

- Floating Point Arithmetic IEEE 754 in Intervals

- Linear systems

- Polynomial Interpolation

- Matrix and Vector Multiplication

- Numerical Integration

- Polynomial Approximation

## Projects

The projects are divided into the following folders:

- `ep1`: Floating Point Arithmetic IEEE 754 in Intervals;

- `ep2`: Solving Linear systems by Gaussian Elimination in 3 strategies;

- `ep3`: Polynomial Interpolation by Lagrange and Newton methods;

- `ep4`: Matrix and Vector Multiplication with UNROLL & JAM and LOOP BLOCKING optimizations;

- `ep5`: Numerical Integration of the Styblinski-Tang function using Monte Carlo and rectangle methods;

- `t1`: Polynomial Approximation by Minimization of the Least Squares Method using Floating Point intervals;

- `t2`: t1 with optimizations;

All projects have a `Makefile` to compile the code. To compile the code, just run `make` in the project folder and remember to read the `README.md` file in each folder to understand how to run the code. Also some submodules have a `REPORT.pdf` file, read it to understand the code and the likwid results in charts.

Most of them also require Likwid to be installed. To install it, follow the instructions in the [official repository](https://github.com/RRZE-HPC/likwid).

## Authors

- [Marcelo Schreiber](https://github.com/marcelo-schreiber)

- [Felipe Vieira](https://github.com/felipeqvieira)