Introduction to Parallel Computing - Deliverable 1

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Table of Contents

• Introduction to Parallel Computing - Deliverable 1
• Table of Contents
• Project Structure
• How to Reproduce
  • On HPC Cluster
  • On your local machine
  • Data Analysis

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Project Structure

├── docs
│   ├── report.pdf
│   ├── res/plots
│       ├── *.png
├──inc
│   ├── matrix_operations.h
│   ├── test.h
│   ├── utils.h
├── out
│   ├── data
│       ├── *.csv
│   ├── err.e
│   ├── out.o
├── src
│   ├── main.c
│   ├── matrix_operations.c
│   ├── test.c
│   ├── utils.c
│   ├── performance_analysis.ipynb
├── .gitignore
├── CMakeLists.txt
├── IPC_homework.pbs
├── README.md

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How to Reproduce

On HPC Cluster

Prerequisites

• Access to the HPC cluster (in this case of the University of Trento)
• SSH client

Steps

1. Open an ssh session on University of Trento's HPC cluster, in your preferred terminal

$ ssh <username>@hpc.unitn.it

2. Clone the repository

$ git clone https://github.com/chiarasabaini/parco-homework.git

3. Navigate the the repository folder

$ cd parco-homework/

3. Run the following command:

$ qsub IPC_homework.pbs

On your local machine

Prerequisites

• CMake
• Make
• C Compiler

Steps

1. Clone the repository

$ git clone https://github.com/chiarasabaini/parco-homework.git

2. Navigate the the repository folder

$ cd parco-homework/

3. Create a build directory

$ mkdir build

4. Navigate to the build directory

$ cd build/

5. Run the following commands:

$ cmake ..
$ make

6. Run the executable

$ ./project.exe

Data Analysis

You will find all of the .csv files containing the data inside the data/ folder. You can process the data and plot the graphs using the provided Jupyter Notebook in the src/ folder.

Happy testing!