Change julia kernel version for MPI collectives notebook

Update BestieTemplate.jl URL to JuliaBesties

.github/workflows/CI.yml

@@ -0,0 +1,64 @@
+name: CI
+on:
+  push:
+    branches:
+      - main
+    tags: ['*']
+  pull_request:
+concurrency:
+  # Skip intermediate builds: always.
+  # Cancel intermediate builds: only if it is a pull request build.
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: ${{ startsWith(github.ref, 'refs/pull/') }}
+jobs:
+  test:
+    name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }} - ${{ github.event_name }}
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        version:
+          - '1.9'
+        os:
+          - ubuntu-latest
+        arch:
+          - x64
+    steps:
+      - uses: actions/checkout@v3
+      - uses: julia-actions/setup-julia@v1
+        with:
+          version: ${{ matrix.version }}
+          arch: ${{ matrix.arch }}
+      - uses: julia-actions/cache@v1
+      - uses: julia-actions/julia-buildpkg@v1
+      - uses: julia-actions/julia-runtest@v1
+  docs:
+    name: Documentation
+    runs-on: ubuntu-latest
+    permissions:
+      contents: write
+      statuses: write
+    steps:
+      - uses: actions/checkout@v3
+      - uses: julia-actions/setup-julia@v1
+        with:
+          version: '1'
+      - name: Set up Python
+        uses: actions/setup-python@v4.7.0
+        with:
+          python-version: '3.9'
+      - name: Install nbconvert
+        run: |
+          python -m pip install jupyter nbconvert 
+      - name: Configure doc environment
+        run: |
+          julia --project=docs/ -e '
+            using Pkg
+            Pkg.develop(PackageSpec(path=pwd()))
+            Pkg.instantiate()'
+      - uses: julia-actions/julia-buildpkg@v1
+      - uses: julia-actions/julia-docdeploy@v1
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
+

.gitignore

@@ -0,0 +1,8 @@
+*.swp
+Manifest.toml
+.ipynb_checkpoints/
+.vscode/
+docs/src/notebooks/
+docs/src/notebook-html/
+*.code-workspace
+*.DS_Store

LICENSE.md

@@ -0,0 +1,395 @@
+Attribution 4.0 International
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Project.toml

@@ -0,0 +1,8 @@
+name = "XM_40017"
+uuid = "97f213cd-d64a-481d-bc9d-afa871b8c535"
+authors = ["Francesc Verdugo <f.verdugo.rojano@vu.nl>"]
+version = "0.1.0"
+
+[deps]
+Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+Glob = "c27321d9-0574-5035-807b-f59d2c89b15c"

README.md

@@ -0,0 +1,6 @@
+# XM_40017
+Jupyter notebook scripts for the course Programming Large-Scale Parallel Systems (XM_40017) at Vrije Universiteit Amsterdam. 
+
+- [**Go to webpage**](https://fverdugo.github.io/XM_40017/dev)
+
+NB: The `notebooks` folder contains material under construction. The material that is ready for study is the one accessible from the website. The material will be added incrementally to the website as the course advances.

dev/.documenter-siteinfo.json

@@ -1 +0,0 @@
-{"documenter":{"julia_version":"1.11.7","generation_timestamp":"2025-09-24T05:37:55","documenter_version":"1.14.1"}}

dev/assets/themeswap.js

@@ -1,84 +0,0 @@
-// Small function to quickly swap out themes. Gets put into the <head> tag..
-function set_theme_from_local_storage() {
-  // Initialize the theme to null, which means default
-  var theme = null;
-  // If the browser supports the localstorage and is not disabled then try to get the
-  // documenter theme
-  if (window.localStorage != null) {
-    // Get the user-picked theme from localStorage. May be `null`, which means the default
-    // theme.
-    theme = window.localStorage.getItem("documenter-theme");
-  }
-  // Check if the users preference is for dark color scheme
-  var darkPreference =
-    window.matchMedia("(prefers-color-scheme: dark)").matches === true;
-  // Initialize a few variables for the loop:
-  //
-  //  - active: will contain the index of the theme that should be active. Note that there
-  //    is no guarantee that localStorage contains sane values. If `active` stays `null`
-  //    we either could not find the theme or it is the default (primary) theme anyway.
-  //    Either way, we then need to stick to the primary theme.
-  //
-  //  - disabled: style sheets that should be disabled (i.e. all the theme style sheets
-  //    that are not the currently active theme)
-  var active = null;
-  var disabled = [];
-  var primaryLightTheme = null;
-  var primaryDarkTheme = null;
-  for (var i = 0; i < document.styleSheets.length; i++) {
-    var ss = document.styleSheets[i];
-    // The <link> tag of each style sheet is expected to have a data-theme-name attribute
-    // which must contain the name of the theme. The names in localStorage much match this.
-    var themename = ss.ownerNode.getAttribute("data-theme-name");
-    // attribute not set => non-theme stylesheet => ignore
-    if (themename === null) continue;
-    // To distinguish the default (primary) theme, it needs to have the data-theme-primary
-    // attribute set.
-    if (ss.ownerNode.getAttribute("data-theme-primary") !== null) {
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-    // Check if the theme is primary dark theme so that we could store its name in darkTheme
-    if (ss.ownerNode.getAttribute("data-theme-primary-dark") !== null) {
-      primaryDarkTheme = themename;
-    }
-    // If we find a matching theme (and it's not the default), we'll set active to non-null
-    if (themename === theme) active = i;
-    // Store the style sheets of inactive themes so that we could disable them
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-      console.error("Unable to determine primary theme.");
-      return;
-    }
-    // When switching to the primary light theme, then we must not have a class name
-    // for the <html> tag. That's only for non-primary or the primary dark theme.
-    if (darkPreference) {
-      document.getElementsByTagName("html")[0].className =
-        "theme--" + activeTheme;
-    } else {
-      document.getElementsByTagName("html")[0].className = "";
-    }
-  }
-  for (var i = 0; i < document.styleSheets.length; i++) {
-    var ss = document.styleSheets[i];
-    // The <link> tag of each style sheet is expected to have a data-theme-name attribute
-    // which must contain the name of the theme. The names in localStorage much match this.
-    var themename = ss.ownerNode.getAttribute("data-theme-name");
-    // attribute not set => non-theme stylesheet => ignore
-    if (themename === null) continue;
-    // we'll disable all the stylesheets, except for the active one
-    ss.disabled = !(themename == activeTheme);
-  }
-}
-set_theme_from_local_storage();

dev/assets/warner.js

@@ -1,68 +0,0 @@
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-  ) {
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-  if (!/v(\d+\.)*\d+/.test(window.DOCUMENTER_CURRENT_VERSION)) {
-    return;
-  }
-
-  // Current version is newest version, so no need to add a warning.
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-    return;
-  }
-
-  // Add a noindex meta tag (unless one exists) so that search engines don't index this version of the docs.
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-  warningMessage +=
-    '<a href="' +
-    href +
-    '">Click here to go to the documentation for the latest stable release.</a>';
-
-  div.innerHTML = warningMessage;
-  div.appendChild(closer);
-  document.body.appendChild(div);
-}
-
-if (document.readyState === "loading") {
-  document.addEventListener("DOMContentLoaded", maybeAddWarning);
-} else {
-  maybeAddWarning();
-}

dev/siteinfo.js

@@ -1,2 +0,0 @@
-var DOCUMENTER_CURRENT_VERSION = "dev";
-var DOCUMENTER_IS_DEV_VERSION = true;

docs/.gitignore

@@ -0,0 +1,8 @@
+build/
+site/
+src/notebook-output/
+src/notebooks/
+Manifest.toml
+src/*.ipynb
+src/*/index.html
+src/*.md

docs/Project.toml

@@ -0,0 +1,4 @@
+[deps]
+Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+Glob = "c27321d9-0574-5035-807b-f59d2c89b15c"
+XM_40017 = "97f213cd-d64a-481d-bc9d-afa871b8c535"

docs/make.jl

@@ -0,0 +1,139 @@
+using XM_40017
+using Documenter
+using Glob 
+
+const md_nb_template = """
+```@meta
+EditURL = "https://github.com/fverdugo/XM_40017/blob/main/notebooks/SCRIPT_NAME.ipynb"
+```
+
+```@raw html
+<div class="admonition is-success">
+    <header class="admonition-header">Tip</header>
+    <div class="admonition-body">
+        <ul>
+            <li>
+                Download this notebook and run it locally on your machine [highly recommended]. Click <a href="https://www.francescverdugo.com/XM_40017/dev/SCRIPT_NAME.ipynb" download>here</a>.
+            </li>
+        </ul>
+    </div>
+</div>
+```
+
+```@raw html
+<iframe id="notebook" src="../SCRIPT_NAME_src/" style="width:100%"></iframe>
+<script>
+  document.addEventListener('DOMContentLoaded', function(){
+    var myIframe = document.getElementById("notebook");
+    iFrameResize({log:true}, myIframe);	
+});
+</script>
+```
+"""
+
+function convert_embedded_img_to_base64(notebook_path)
+    doc = open(io->read(io, String), notebook_path)
+    # Regex matching: extract filename and base64 code
+    regex = r"attachments\\\":\s*\{\s*\\\"(?<filename>.*).png\\\":\s*\{\s*\\\"image/png\\\":\s*\\\"(?<base64code>.*)\\\""
+    res = eachmatch(regex, doc)
+    matches = collect(res)
+    # Replace img src with base64 code
+    for m in matches
+        filename = m[:filename]
+        base64 = m[:base64code]
+        doc = replace(doc, "attachment:$filename.png" => "data:image/png;base64,$base64")
+    end
+    filename = splitpath(notebook_path)[end]  
+    open("docs/src/$filename","w") do f
+        write(f, doc)
+    end
+end
+
+# Write markdown file that includes notebook html
+function create_md_nb_file( filename )
+    global md_nb_template;
+    content = replace(md_nb_template, "SCRIPT_NAME" => filename)
+    md_path = joinpath(@__DIR__, "src", filename * ".md" ) 
+    open(md_path, "w") do md_file
+        write(md_file, content)
+    end
+    return md_path
+end
+
+# Convert to html using nbconvert
+function convert_notebook_to_html(notebook_path; output_name,output_dir, theme = "light")
+    command_jup = "jupyter"
+    command_nbc = "nbconvert"
+    output_format = "--to=html"
+    theme = "--theme=$theme"
+    output = "--output=$output_name"
+    output_dir = "--output-dir=$output_dir"
+    infile = notebook_path
+    run(`$command_jup $command_nbc $output_format $output $output_dir $theme $infile`)
+end
+
+# Modify html contents
+function modify_notebook_html( html_filepath )
+    content = open( html_filepath, "r" ) do html_file 
+        read( html_file, String )
+    end
+    # Resize iframes using IframeResizer
+    content = replace(content, 
+        r"(<script\b[^>]*>[\s\S]*?<\/script>\K)" => 
+        s"\1\n\t<script src='../assets/iframeResizer.contentWindow.min.js'></script>\n";
+        count = 1
+    )
+    open( html_filepath, "w" ) do html_file
+        write( html_file, content )
+    end
+    return nothing
+end
+
+
+# Loop over notebooks and generate html and markdown 
+repo_root = joinpath(@__DIR__,"..") |> normpath
+notebook_files = glob("*.ipynb", joinpath(repo_root,"notebooks/"))
+for filepath in notebook_files
+    #continue
+    convert_embedded_img_to_base64(filepath)
+    filename_with_ext = splitpath(filepath)[end]    
+    filename = splitext(filename_with_ext)[1]
+    pth = mkpath(joinpath(repo_root,"docs","src",filename*"_src"))
+    create_md_nb_file(filename)
+    convert_notebook_to_html("docs/src/$filename_with_ext", output_dir=pth, output_name = "index")
+    modify_notebook_html("docs/src/$(filename)_src/index.html")
+end
+
+makedocs(;
+    modules=[XM_40017],
+    authors="Francesc Verdugo <f.verdugo.rojano@vu.nl>",
+    repo="https://github.com/fverdugo/XM_40017/blob/{commit}{path}#{line}",
+    sitename="XM_40017",    
+    format=Documenter.HTML(;
+        assets = ["assets/favicon.ico", "assets/iframeResizer.min.js", "assets/custom.css"],
+        prettyurls=get(ENV, "CI", "false") == "true",
+        canonical="https://fverdugo.github.io/XM_40017",
+        edit_link="main",),
+    pages=["Home" => "index.md","Getting started"=>"getting_started_with_julia.md",
+           "Notebooks"=>[
+                         "Julia Basics" => "julia_basics.md",
+                         "Asynchronous programming in Julia" => "julia_async.md",
+                         "Distributed computing in Julia" => "julia_distributed.md",
+                         #"Distributed computing with MPI" => "mpi_tutorial.md",
+                         "Matrix-matrix multiplication"=>"matrix_matrix.md",
+                         "MPI (point-to-point)" => "julia_mpi.md",
+                         "MPI (collectives)" => "mpi_collectives.md",
+                         "Jacobi method" => "jacobi_method.md",
+                         "All pairs of shortest paths" => "asp.md",
+                         "Gaussian elimination" => "LEQ.md",
+                         "Traveling salesperson problem" => "tsp.md",
+                         #"Partial differential equations" => "pdes.md",
+                         ],
+          "Solutions" => "solutions_for_all_notebooks.md",
+          ],
+)
+
+deploydocs(;
+    repo="github.com/fverdugo/XM_40017",
+    devbranch="main",
+)

docs/src/getting_started_with_julia.md

@@ -0,0 +1,435 @@
+# Getting started
+
+
+## Introduction
+
+The programming of this course will be done using the [Julia programming language](https://julialang.org). Thus, we start by explaining how to get up and running with Julia. After studying this page, you will be able to:
+
+- Use the Julia REPL,
+- Run serial and parallel code,
+- Install and manage Julia packages.
+
+## Why Julia?
+
+Courses related with high-performance computing (HPC) often use languages such as C, C++, or Fortran. We use Julia instead to make the course accessible to a wider set of students, including the ones that have no experience with 
+C/C++ or Fortran, but are willing to learn parallel programming. Julia is a relatively new programming language specifically designed for scientific computing. It combines a high-level syntax close to interpreted languages like Python with the performance of compiled languages like C, C++, or Fortran. Thus, Julia will allow us to write efficient parallel algorithms with a syntax that is convenient in a teaching setting. In addition, Julia provides easy access to different programming models to write distributed algorithms, which will be useful to learn and experiment with them.
+
+!!! tip
+    You can run the code [in this link](https://github.com/JuliaAcademy/JuliaTutorials/blob/724e15a350d150a9773afe51a3830709dbed422f/introductory-tutorials/intro-to-julia/09.%20Julia%20is%20fast.ipynb) to learn how Julia compares to other languages (C and Python) in terms of performance.
+
+
+## Installing Julia
+
+This is a tutorial-like page. Follow these steps before you continue reading the document.
+
+- Download and install Julia from [julialang.org](https://julialang.org);
+- Follow the specific instructions for your operating system: [Windows](https://julialang.org/downloads/platform/#windows), [MacOS](https://julialang.org/downloads/platform/#macos), or [Linux](https://julialang.org/downloads/platform/#linux_and_freebsd)
+- Download and install [VSCode and its Julia extension](https://www.julia-vscode.org/docs/dev/gettingstarted/);
+
+
+## The Julia REPL
+
+### Starting Julia
+
+There are several ways of opening Julia depending on your operating system and your IDE, but it is usually as simple as launching the Julia app. With VSCode, open a folder (File > Open Folder). Then,  press `Ctrl`+`Shift`+`P` to open the command bar, and execute `Julia: Start REPL`. If this does not work, make sure you have the Julia extension for VSCode installed. Independently of the method you use, opening Julia results in a window with some text ending with:
+
+```
+julia>
+```
+
+You have just opened the Julia *read-evaluate-print loop*, or simply the Julia *REPL*. Congrats! You will spend most of time using the REPL, when working in Julia. The REPL is a console waiting for user input. Just as in other consoles, the string of text right before the input area (`julia>` in the case) is called the *command prompt* or simply the *prompt*.
+
+### Basic usage
+
+The usage of the REPL is as follows:
+- You write some input
+- press enter
+- you get the output
+
+For instance, try this
+
+```julia
+julia> 1 + 1
+```
+
+A "Hello world" example looks like this in Julia
+
+```julia
+julia> println("Hello, world!")
+```
+
+Try to run it in the REPL.
+
+### Help mode
+
+Curious about what the function `println` does? Enter into *help* mode to look into the documentation. This is done by typing a question mark (`?`) into the input field:
+
+```julia
+julia> ?
+```
+
+After typing `?`, the command prompt changes to `help?>`. It means we are in help mode. Now, we can type a function name to see its documentation.
+
+```julia
+help?> println
+```
+
+### Package and shell modes
+
+The REPL comes with two more modes, namely *package* and *shell* modes. To enter package mode type
+
+```julia
+julia> ]
+```
+
+Package mode is used to install and manage packages. We are going to discuss the package mode in greater detail later. To return back to normal mode press the backspace key several times.
+
+To enter shell mode type semicolon (`;`)
+```julia
+julia> ;
+```
+The prompt should have changed to `shell>` indicating that we are in shell mode. Now you can type commands that you would normally do on your system command line. For instance,
+
+```julia
+shell> ls
+```
+will display the contents of the current folder in Mac or Linux. Using shell mode in Windows is not straightforward, and thus not recommended for beginners.
+
+
+
+## Running Julia code
+
+### Running more complex code
+
+Real-world Julia programs are not typed in the REPL in practice. They are written in one or more files and *included* in the REPL. To try this, create a new file called `hello.jl`, write the code of the "Hello world" example above, and save it. If you are using VSCode, you can create the file using File > New File > Julia File. Once the file is saved with the name `hello.jl`, execute it as follows
+
+```julia
+julia> include("hello.jl")
+```
+
+!!! warning
+    Make sure that the file `"hello.jl"` is located in the current working directory of your Julia session. You can query the current directory with function `pwd()`. You can change to another directory with function `cd()` if needed.  Also, make sure that the file extension is `.jl`.
+
+The recommended way of running Julia code is using the REPL as we did. But it is also possible to run code directly from the system command line. To this end, open a terminal and call Julia followed by the path to the file containing the code you want to execute.
+
+```
+$ julia hello.jl
+```
+
+The previous line assumes that you have Julia properly installed in the system and that it's usable from the terminal. In UNIX systems (Linux and Mac), the Julia binary needs to be in one of the directories listed in the `PATH` environment variable. To check that Julia is properly installed, you can use
+
+```
+$ julia --version
+```
+
+If this runs without error and you see a version number, you are good to go!
+
+You can also run julia code from the terminal using the `-e` flag:
+
+```
+$ julia -e 'println("Hello, world!")'
+```
+
+!!! note
+    In this tutorial, when a code snipped starts with `$`, it should be run in the terminal. Otherwise, the code is to be run in the Julia REPL.
+
+!!! tip
+    Avoid calling Julia code from the terminal, use the Julia REPL instead!
+    Each time you call Julia from the terminal, you start a fresh Julia session and Julia will need to compile your code from scratch.
+    This can be time consuming for large projects.
+    In contrast, if you execute code in the REPL, Julia will compile code incrementally, which is much faster.
+    Running code in a cluster (like in DAS-5 for the Julia assignment) is among the few situations you need to run Julia code
+    from the terminal. Visit this link ([Julia workflow tips](https://docs.julialang.org/en/v1/manual/workflow-tips/))
+    from the official Julia documentation for further information about how to develop Julia code effectivelly.
+
+### Running parallel code
+
+
+Since we are in a parallel computing course, let's run a parallel "Hello world" example in Julia. Open a Julia REPL and write
+
+```julia
+julia> using Distributed
+julia> @everywhere println("Hello, world! I am proc $(myid()) from $(nprocs())")
+```
+
+Here, we are using the `Distributed` package, which is part of the Julia standard library that provides distributed memory parallel support. The code prints the process id and the number of processes in the current Julia session.
+
+You will probably only see output from 1 process. We need to add more processes to run the example in parallel. This is done with the `addprocs` function.
+
+```julia
+julia> addprocs(3)
+```
+We have added 3 new processes. Plus the old one, we have 4 processes. Run the code again.
+
+```julia
+julia> @everywhere println("Hello, world! I am proc $(myid()) from $(nprocs())")
+```
+
+Now, you should see output from 4 processes.
+
+It is possible to specify the number of processes when starting Julia from the terminal with the `-p` argument (useful, e.g., when running in a cluster).  If you launch Julia from the terminal as
+
+```
+$ julia -p 3
+```
+and then run
+
+```julia
+julia> @everywhere println("Hello, world! I am proc $(myid()) from $(nprocs())")
+```
+
+You should get output from 4 processes as before.
+
+### Installing packages
+
+One of the most useful features of Julia is its package manager. It allows one to install Julia packages in a straightforward and platform independent way. To illustrate this, let us consider the following parallel "Hello world" example. This example uses the Message Passing Interface (MPI). We will learn more about MPI later in the course.
+
+
+Copy the following block of code into a new file named `"hello_mpi.jl"`
+
+```julia
+# file hello_mpi.jl
+using MPI
+MPI.Init()
+comm = MPI.COMM_WORLD
+rank = MPI.Comm_rank(comm)
+nranks = MPI.Comm_size(comm)
+println("Hello world, I am rank $rank of $nranks")
+```
+
+As you can see from this example, one can access MPI from Julia in a clean way, without type annotations and other complexities of C/C++ code.
+
+Now, run the file from the REPL
+```julia
+julia> include("hello_mpi.jl")
+```
+
+It probably didn't work, right? Read the error message and note that the MPI package needs to be installed to run this code.
+
+To install a package, we need to enter *package* mode. Remember that we entered into help mode by typing `?`. Package mode is activated by typing `]` : 
+```julia
+julia> ]
+```
+At this point, the prompt should have changed to `(@v1.11) pkg>` indicating that we are in package mode. The text between the parentheses indicates which is the active *project*, i.e., where packages are going to be installed. In this case, we are working with the global project associated with our Julia installation (which is Julia 1.11 in this example, but it can be another version in your case).
+
+To install the MPI package, type
+```julia
+(@v1.11) pkg> add MPI
+```
+Congrats, you have installed MPI!
+
+!!! note
+    Many Julia package names end with `.jl`. This is just a way of signaling that a package is written in Julia. When using such packages, the `.jl` needs to be omitted. In this case, we have installed the `MPI.jl` package even though we have only typed `MPI` in the REPL.
+
+!!! note
+    The package you have installed is the Julia interface to MPI, called  `MPI.jl`. Note that it is not an MPI library by itself. It is just a thin wrapper between MPI and Julia. To use this interface, you need an actual MPI library installed in your system such as OpenMPI or MPICH. Julia downloads and installs an MPI library for you, but it is also possible to use an MPI library already available in your system. This is useful, e.g., when running on HPC clusters. See the [documentation](https://juliaparallel.org/MPI.jl/stable/configuration/) of `MPI.jl` for further details.
+
+
+To check that the package was installed properly, exit package mode by pressing the backspace key several times, and run it again
+
+```julia
+julia> include("hello_mpi.jl")
+```
+
+Now, it should work, but you probably get output from a single MPI rank only.
+
+### Running MPI code
+
+To run MPI applications in parallel, you need a launcher like `mpiexec`. MPI codes written in Julia are not an exception to this rule. From the system terminal, you can run
+```
+$ mpiexec -np 4 julia hello_mpi.jl
+```
+But it will probably not work since the version of `mpiexec` needs to match with the MPI version we are using from Julia. Don't worry if you could not make it work! A more elegant way to run MPI code is from the Julia REPL directly, by using these commands:
+```julia
+julia> using MPI
+julia> run(`$(mpiexec()) -np 4 julia hello_mpi.jl`);
+```
+
+Now, you should see output from 4 ranks.
+
+## Package manager
+
+### Installing packages locally
+
+We have installed the `MPI` package globally and it will be available in all Julia sessions. However, in some situations, we want to work with different versions of the same package or to install packages in an isolated way to avoid potential conflicts with other packages. This can be done by using local projects.
+
+A project is simply a folder in your file system. To use a particular folder as your project, you need to *activate* it. This is done by entering package mode and using the `activate` command followed by the path to the folder you want to activate.
+```julia
+(@v1.11) pkg> activate .
+```
+ The previous command will activate the current working directory. Note that the dot `.` is indeed the path to the current folder.
+
+The prompt has changed to `(lessons) pkg>` indicating that we are in the project within the `lessons` folder. The particular folder name can be different in your case.
+
+!!! tip
+    You can activate a project directly when opening Julia from the terminal using the `--project` flag. The command `$ julia --project=.` will open Julia and activate a project in the current directory. You can also achieve the same effect by setting the environment variable  `JULIA_PROJECT` with the path of the folder you want to activate.
+
+!!! note
+    The active project folder and the current working directory are two independent concepts! For instance,  `(@v1.11) pkg> activate folderB` and then `julia> cd("folderA")`, will activate the project in `folderB` and change the current working directory to `folderA`.
+
+At this point all package-related operations will be local to the new project. For instance, install the `DataFrames` package.
+
+```julia
+(lessons) pkg> add DataFrames
+```
+Use the package to check that it is installed
+
+```julia
+julia> using DataFrames
+julia> DataFrame(a=[1,2],b=[3,4])
+```
+Now, we can return to the global project to check that `DataFrames` has not been installed there. To return to the global environment, use `activate` without a folder name.
+
+```julia
+(lessons) pkg> activate
+```
+The prompt is again `(@v1.11) pkg>`
+
+Now, try to use `DataFrames`.
+
+```julia
+julia> using DataFrames
+julia> DataFrame(a=[1,2],b=[3,4])
+```
+You should get an error or a warning unless you already had `DataFrames` installed globally.
+
+### Project and Manifest files
+
+The information about a project is stored in two files `Project.toml` and `Manifest.toml`.
+
+- `Project.toml` contains the packages explicitly installed (the direct dependencies)
+
+- `Manifest.toml` contains direct and indirect dependencies along with the concrete version of each package.
+
+
+In other words, `Project.toml` contains the packages relevant for the user, whereas `Manifest.toml` is the detailed snapshot of all dependencies. The `Manifest.toml` can be used to reproduce the same environment in another machine.
+
+You can see the path to the current `Project.toml` file by using the `status` operator (or `st` in its short form) while in package mode
+
+```julia
+(@v1.11) pkg> status
+```
+
+The information about the `Manifest.toml` can be inspected by passing the `-m` flag.
+
+```julia
+(@v1.11) pkg> status -m
+```
+
+### Installing packages from a project file
+
+Project files can be used to install lists of packages defined by others. E.g., to install all the dependencies of a Julia application.
+
+Assume that a colleague has sent to you a `Project.toml` file with this content:
+
+```
+[deps]
+BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
+DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
+MPI = "da04e1cc-30fd-572f-bb4f-1f8673147195"
+```
+
+Copy the contents of previous code block into a file called  `Project.toml` and place it in an empty folder named `newproject`. It is important that the file is named `Project.toml`. You can create a new folder from the REPL with
+
+```julia
+julia> mkdir("newproject")
+```
+
+To install all the packages registered in this file you need to activate the folder containing your `Project.toml` file
+```julia
+(@v1.11) pkg> activate newproject
+```
+and then *instantiating* it
+```julia
+(newproject) pkg> instantiate
+```
+
+The instantiate command will download and install all listed packages and their dependencies in just one click.
+
+### Getting help in package mode
+
+You can get help about a particular package operator by writing `help` in front of it
+
+```julia
+(@v1.11) pkg> help activate
+```
+
+You can get an overview of all package commands by typing `help` alone
+```julia
+(@v1.11) pkg> help
+```
+
+### Package operations in Julia code
+
+In some situations it is required to use package commands in Julia code, e.g., to automatize installation and deployment of Julia applications. This can be done using the `Pkg` package. For instance
+
+```julia
+julia> using Pkg
+julia> Pkg.status()
+```
+is equivalent to calling `status` in package mode.
+```julia
+(@v1.11) pkg> status
+```
+
+### Creating you own package
+
+In many situations, it is useful to create your own package, for instance, when working with a large code base, when you want to reduce compilation latency using [`Revise.jl`](https://github.com/timholy/Revise.jl),
+or if you want to eventually [register your package](https://github.com/JuliaRegistries/Registrator.jl) and share it with others.
+
+The simplest way of generating a package (called `MyPackage`) is as follows. Open Julia, go to package mode, and type
+
+```julia
+(@v1.11) pkg> generate MyPackage
+```
+
+This will crate a minimal package consisting of a new folder `MyPackage` with two files:
+
+* `MyPackage/Project.toml`: Project file defining the direct dependencies of your package.
+* `MyPackage/src/MyPackage.jl`: Main source file of your package. You can split your code in several files if needed, and include them in the package main file using function `include`.
+
+!!! tip
+    This approach only generates a very minimal package. To create a more sophisticated package skeleton (including unit testing, code coverage, readme file, licence, etc.) use
+    [`PkgTemplates.jl`](https://github.com/JuliaCI/PkgTemplates.jl) or [`BestieTemplate.jl`](https://github.com/JuliaBesties/BestieTemplate.jl). The later one is developed in Amsterdam at the
+    [Netherlands eScience Center](https://www.esciencecenter.nl/).
+
+You can add dependencies to the package by activating the `MyPackage` folder in package mode and adding new dependencies as always:
+
+```julia
+(@v1.11) pkg> activate MyPackage
+(MyPackage) pkg> add MPI
+```
+
+This will add MPI to your package dependencies.
+
+### Using your own package
+
+To use your package you first need to add it to a package environment of your choice. This is done by changing to package mode and typing `develop ` followed by the path to the folder containing the package. For instance:
+
+```julia
+(@v1.11) pkg> develop MyPackage
+```
+
+!!! note
+    You do not need to "develop" your package if you activated the package folder `MyPackage`.
+
+Now, we can go back to standard Julia mode and use it as any other package:
+
+```julia
+using MyPackage
+MyPackage.greet()
+```
+
+Here, we just called the example function defined in `MyPackage/src/MyPackage.jl`.
+
+
+## Conclusion
+
+We have learned the basics of how to work with Julia, including how to run serial and parallel code, and how to manage, create, and use Julia packages.
+This knowledge will allow you to follow the course effectively!
+If you want to further dig into the topics we have covered here, you can take a look at the following links:
+
+- [Julia Manual](https://docs.julialang.org/en/v1/manual/getting-started/)
+- [Package manager](https://pkgdocs.julialang.org/v1/getting-started/)
+
+

docs/src/index.md

@@ -0,0 +1,57 @@
+```@meta
+CurrentModule = XM_40017
+```
+# Programming Large-Scale Parallel Systems (XM_40017)
+
+Welcome to the interactive lecture notes of the [Programming Large-Scale Parallel Systems course](https://studiegids.vu.nl/EN/courses/2023-2024/XM_40017#/) at [VU Amsterdam](https://vu.nl)!
+
+## What
+
+This page contains part of the course material of the Programming Large-Scale Parallel Systems course at VU Amsterdam.
+We provide several lecture notes in jupyter notebook format, which will help you to learn how to design, analyze, and program parallel algorithms on multi-node computing systems.
+Further information about the course is found in the study guide
+([click here](https://studiegids.vu.nl/en/vakken/2025-2026/XM_40017#/)) and our Canvas page (for registered students).
+
+!!! note
+    Material will be added incrementally to the website as the course advances.
+
+!!! warning
+    This page will eventually contain only a part of the course material. The rest will be available on Canvas. In particular, **the material in this public webpage does not fully cover all topics in the final exam**.
+
+## How to use this page
+
+You have two main ways of studying the notebooks:
+
+- Download the notebooks and run them locally on your computer (recommended). At each notebook page you will find a green box with links to download the notebook.
+- You also have the static version of the notebooks displayed in this webpage for quick reference.
+
+## How to run the notebooks locally
+
+To run a notebook locally follow these steps:
+
+- Install Julia (if not done already). More information in [Getting started](@ref).
+- Download the notebook.
+- Launch Julia. More information in [Getting started](@ref).
+- Execute these commands in the Julia command line:
+
+```
+julia> using Pkg
+julia> Pkg.add("IJulia")
+julia> using IJulia
+julia> notebook()
+```
+- These commands will open a jupyter in your web browser. Navigate in jupyter to the notebook file you have downloaded and open it.
+
+## Authors
+
+This material is created by [Francesc Verdugo](https://github.com/fverdugo/) with the help of [Gelieza Kötterheinrich](https://www.linkedin.com/in/gelieza-k/). Part of the notebooks are based on the course slides by [Henri Bal](https://www.vuhpdc.net/henri-bal/).
+
+
+## License
+
+All material on this page that is original to this course may be used under a [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) license.
+
+
+## Acknowledgment
+
+This page was created with the support of the Faculty of Science of [Vrije Universiteit Amsterdam](https://vu.nl) in the framework of the project "Interactive lecture notes and exercises for the Programming Large-Scale Parallel Systems course" funded by the "Innovation budget BETA 2023 Studievoorschotmiddelen (SVM) towards Activated Blended Learning".

docs/src/solutions_for_all_notebooks.md

@@ -0,0 +1,445 @@
+# Solutions
+
+## Julia Basics
+
+### Exercise 1
+
+```julia
+function ex1(a)
+    j = 1
+    m = a[j]
+    for (i,ai) in enumerate(a)
+        if m < ai
+            m = ai
+            j = i
+        end
+    end
+    (m,j)
+end
+```
+
+### Exercise 2
+
+```julia
+ex2(f,g) = x -> f(x) + g(x)
+```
+
+### Exercise 3
+
+```julia
+n = 1000
+x = LinRange(-1.7,0.7,n)
+y = LinRange(-1.2,1.2,n)
+values = zeros(n,n)
+for j in 1:n
+    for i in 1:n
+        values[i,j] = surprise(x[i],y[j])
+    end
+end
+using GLMakie
+heatmap(x,y,values)
+```
+
+## Asynchronous programming in Julia
+
+## Distributed computing in Julia
+
+### Exercise 1
+
+```julia
+f = () -> Channel{Int}(1)
+worker_ids = workers()
+chnls = [ RemoteChannel(f,w) for w in worker_ids ]
+@sync for (iw,w) in enumerate(worker_ids)
+    @spawnat w begin
+        chnl_snd = chnls[iw]
+        if iw == 1
+            chnl_rcv = chnls[end]
+            msg = 2
+            println("msg = $msg")
+            put!(chnl_snd,msg)
+            msg = take!(chnl_rcv)
+            println("msg = $msg")
+        else
+           chnl_rcv = chnls[iw-1]
+           msg = take!(chnl_rcv)
+           msg += 1
+           println("msg = $msg")
+           put!(chnl_snd,msg)
+        end
+    end
+end
+```
+
+This is another possible solution that does not use remote channels.
+
+```julia
+@everywhere function work(msg,iw,worker_ids)
+    println("msg = $msg")
+    if iw < length(worker_ids)
+        inext = iw+1
+        next = worker_ids[iw+1]
+        @fetchfrom next work(msg+1,inext,worker_ids)
+    else
+        @fetchfrom worker_ids[1] println("msg = $msg")
+    end
+    return nothing
+end
+msg = 2
+iw = 1
+worker_ids = workers()
+@fetchfrom worker_ids[iw] work(msg,iw,worker_ids)
+```
+
+## Matrix-matrix multiplication
+
+### Exercise 1
+
+```julia
+function matmul_dist_3!(C,A,B)
+    m = size(C,1)
+    n = size(C,2)
+    l = size(A,2)
+    @assert size(A,1) == m
+    @assert size(B,2) == n
+    @assert size(B,1) == l
+    @assert mod(m,nworkers()) == 0
+    nrows_w = div(m,nworkers())
+    @sync for (iw,w) in enumerate(workers())
+        lb = 1 + (iw-1)*nrows_w
+        ub = iw*nrows_w
+        A_w = A[lb:ub,:]
+        ftr = @spawnat w begin
+             C_w = similar(A_w)
+             matmul_seq!(C_w,A_w,B)
+             C_w
+        end
+        @async C[lb:ub,:] = fetch(ftr)
+    end
+    C
+end
+
+@everywhere function matmul_seq!(C,A,B)
+    m = size(C,1)
+    n = size(C,2)
+    l = size(A,2)
+    @assert size(A,1) == m
+    @assert size(B,2) == n
+    @assert size(B,1) == l
+    z = zero(eltype(C))
+    for j in 1:n
+        for i in 1:m
+            Cij = z
+            for k in 1:l
+                @inbounds Cij = Cij + A[i,k]*B[k,j]
+            end
+            C[i,j] = Cij
+        end
+    end
+    C
+end
+```
+
+## MPI (Point-to-point)
+
+### Exercise 1
+
+```julia
+function matmul_mpi_3!(C,A,B)
+    comm = MPI.COMM_WORLD
+    rank = MPI.Comm_rank(comm)
+    P = MPI.Comm_size(comm)
+    if  rank == 0
+        N = size(A,1)
+        myB = B
+        for dest in 1:(P-1)
+            MPI.Send(B,comm;dest)
+        end
+    else
+        source = 0
+        status = MPI.Probe(comm,MPI.Status;source)
+        count = MPI.Get_count(status,eltype(B))
+        N = Int(sqrt(count))
+        myB = zeros(N,N)
+        MPI.Recv!(myB,comm;source)
+    end
+    L = div(N,P)
+    myA = zeros(L,N)
+    if  rank == 0
+        lb = L*rank+1
+        ub = L*(rank+1)
+        myA[:,:] = view(A,lb:ub,:)
+        for dest in 1:(P-1)
+            lb = L*dest+1
+            ub = L*(dest+1)
+            MPI.Send(view(A,lb:ub,:),comm;dest)
+        end
+    else
+        source = 0
+        MPI.Recv!(myA,comm;source)
+    end
+    myC = myA*myB
+    if rank == 0
+        lb = L*rank+1
+        ub = L*(rank+1)
+        C[lb:ub,:] = myC
+        for source in 1:(P-1)
+            lb = L*source+1
+            ub = L*(source+1)
+            MPI.Recv!(view(C,lb:ub,:),comm;source)
+        end
+    else
+        dest = 0
+        MPI.Send(myC,comm;dest)
+    end
+    C
+end
+```
+
+### Exercise 2
+
+```julia
+using MPI
+MPI.Init()
+comm = MPI.COMM_WORLD
+rank = MPI.Comm_rank(comm)
+nranks = MPI.Comm_size(comm)
+buffer = Ref(0)
+if rank == 0
+    msg = 2
+    buffer[] = msg
+    println("msg = $(buffer[])")
+    MPI.Send(buffer,comm;dest=rank+1,tag=0)
+    MPI.Recv!(buffer,comm;source=nranks-1,tag=0)
+    println("msg = $(buffer[])")
+else
+    dest = if (rank != nranks-1)
+        rank+1
+    else
+        0
+    end
+    MPI.Recv!(buffer,comm;source=rank-1,tag=0)
+    buffer[] += 1
+    println("msg = $(buffer[])")
+    MPI.Send(buffer,comm;dest,tag=0)
+end
+```
+## MPI (collectives)
+
+### Exercise 1
+
+```julia
+function matmul_mpi_3!(C,A,B)
+    comm = MPI.COMM_WORLD
+    rank = MPI.Comm_rank(comm)
+    P = MPI.Comm_size(comm)
+    root = 0
+    if  rank == root
+        N = size(A,1)
+        Nref = Ref(N)
+    else
+        Nref = Ref(0)
+    end
+    MPI.Bcast!(Nref,comm;root)
+    N = Nref[]
+    if  rank == root
+        myB = B
+    else
+        myB = zeros(N,N)
+    end
+    MPI.Bcast!(myB,comm;root)
+    L = div(N,P)
+    # Tricky part
+    # Julia works "col major"
+    myAt = zeros(N,L)
+    At = collect(transpose(A))
+    MPI.Scatter!(At,myAt,comm;root)
+    myCt = transpose(myB)*myAt
+    Ct = similar(C)
+    MPI.Gather!(myCt,Ct,comm;root)
+    C .= transpose(Ct)
+    C
+end
+```
+
+This other solution uses a column partition instead of a row partition.
+It is more natural to work with column partitions in Julia if possible since matrices are
+in "col major" format. Note that we do not need all the auxiliary transposes anymore.
+
+```julia
+function matmul_mpi_3!(C,A,B)
+    comm = MPI.COMM_WORLD
+    rank = MPI.Comm_rank(comm)
+    P = MPI.Comm_size(comm)
+    root = 0
+    if  rank == root
+        N = size(A,1)
+        Nref = Ref(N)
+    else
+        Nref = Ref(0)
+    end
+    MPI.Bcast!(Nref,comm;root)
+    N = Nref[]
+    if  rank == root
+        myA = A
+    else
+        myA = zeros(N,N)
+    end
+    MPI.Bcast!(myA,comm;root)
+    L = div(N,P)
+    myB = zeros(N,L)
+    MPI.Scatter!(B,myB,comm;root)
+    myC = myA*myB
+    MPI.Gather!(myC,C,comm;root)
+    C
+end
+```
+
+## Jacobi method
+
+### Exercise 1
+
+```julia
+function jacobi_mpi(n,niters)
+    u, u_new = init(n,comm)
+    load = length(u)-2
+    rank = MPI.Comm_rank(comm)
+    nranks = MPI.Comm_size(comm)
+    nreqs = 2*((rank != 0) + (rank != (nranks-1)))
+    reqs = MPI.MultiRequest(nreqs)
+    for t in 1:niters
+        ireq = 0
+        if rank != 0
+            neig_rank = rank-1
+            u_snd = view(u,2:2)
+            u_rcv = view(u,1:1)
+            dest = neig_rank
+            source = neig_rank
+            ireq += 1
+            MPI.Isend(u_snd,comm,reqs[ireq];dest)
+            ireq += 1
+            MPI.Irecv!(u_rcv,comm,reqs[ireq];source)
+        end
+        if rank != (nranks-1)
+            neig_rank = rank+1
+            u_snd = view(u,(load+1):(load+1))
+            u_rcv = view(u,(load+2):(load+2))
+            dest = neig_rank
+            source = neig_rank
+            ireq += 1
+            MPI.Isend(u_snd,comm,reqs[ireq];dest)
+            ireq += 1
+            MPI.Irecv!(u_rcv,comm,reqs[ireq];source)
+        end
+        # Upload interior cells
+        for i in 3:load
+            u_new[i] = 0.5*(u[i-1]+u[i+1])
+        end
+        # Wait for the communications to finish
+        MPI.Waitall(reqs)
+        # Update boundaries
+        for i in (2,load+1)
+            u_new[i] = 0.5*(u[i-1]+u[i+1])
+        end
+        u, u_new = u_new, u
+    end
+    return u
+end
+```
+
+### Exercise 2
+
+```julia
+function jacobi_mpi(n,niters,tol,comm) # new tol arg
+    u, u_new = init(n,comm)
+    load = length(u)-2
+    rank = MPI.Comm_rank(comm)
+    nranks = MPI.Comm_size(comm)
+    nreqs = 2*((rank != 0) + (rank != (nranks-1)))
+    reqs = MPI.MultiRequest(nreqs)
+    for t in 1:niters
+        ireq = 0
+        if rank != 0
+            neig_rank = rank-1
+            u_snd = view(u,2:2)
+            u_rcv = view(u,1:1)
+            dest = neig_rank
+            source = neig_rank
+            ireq += 1
+            MPI.Isend(u_snd,comm,reqs[ireq];dest)
+            ireq += 1
+            MPI.Irecv!(u_rcv,comm,reqs[ireq];source)
+        end
+        if rank != (nranks-1)
+            neig_rank = rank+1
+            u_snd = view(u,(load+1):(load+1))
+            u_rcv = view(u,(load+2):(load+2))
+            dest = neig_rank
+            source = neig_rank
+            ireq += 1
+            MPI.Isend(u_snd,comm,reqs[ireq];dest)
+            ireq += 1
+            MPI.Irecv!(u_rcv,comm,reqs[ireq];source)
+        end
+        MPI.Waitall(reqs)
+        # Compute the max diff in the current
+        # rank while doing the local update
+        mydiff = 0.0
+        for i in 2:load+1
+            u_new[i] = 0.5*(u[i-1]+u[i+1])
+            diff_i = abs(u_new[i] - u[i])
+            mydiff = max(mydiff,diff_i)
+        end
+        # Now we need to find the global diff
+        diff_ref = Ref(mydiff)
+        MPI.Allreduce!(diff_ref,max,comm)
+        diff = diff_ref[]
+        # If global diff below tol, stop!
+        if diff < tol
+            return u_new
+        end
+        u, u_new = u_new, u
+    end
+    return u
+end
+```
+
+## All pairs of shortest paths
+
+### Exercise 1
+
+```julia
+function floyd_iterations!(myC,comm)
+    L = size(myC,1)
+    N = size(myC,2)
+    rank = MPI.Comm_rank(comm)
+    P = MPI.Comm_size(comm)
+    lb = L*rank+1
+    ub = L*(rank+1)
+    C_k = similar(myC,N)
+    for k in 1:N
+        if (lb<=k) && (k<=ub)
+            # If I have the row, fill in the buffer
+            myk = (k-lb)+1
+            C_k[:] = view(myC,myk,:)
+        end
+        # We need to find out the owner of row k.
+        # Easy since N is a multiple of P
+        root = div(k-1,L)
+        MPI.Bcast!(C_k,comm;root)
+        # Now, we have the data dependencies and
+        # we can do the updates locally
+        for j in 1:N
+            for i in 1:L
+                myC[i,j] = min(myC[i,j],myC[i,k]+C_k[j])
+            end
+        end
+    end
+    myC
+end
+```
+
+
+
+
+

index.html

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