31d820d3 Fix typos

notebooks/3b--Software_Engineering.ipynb

@@ -158,7 +158,7 @@
     "* source code\n",
     "* installation routines (`setup.py`)\n",
     "* user documentation - how to use the package\n",
-    "* develper documentation - how to develop code for the package\n",
+    "* developer documentation - how to develop code for the package\n",
     "* software tests\n",
     "* commonly expected text files to help people get information quickly (e.g. on public repositories)\n",
     "    * `README`\n",
@@ -320,11 +320,11 @@
    "source": [
     "## Testing\n",
     "* Tests are a central part of the software development life cycle\n",
-    "    * Avoid regression\n",
-    "    * Facilitate collaboration\n",
+    "    * avoid regression\n",
+    "    * facilitate collaboration\n",
     "* **Continuous integration**:\n",
     "    * merge contributions often\n",
-    "    * run tests automatically at each code commit, e.g. via GitLab-CI\n",
+    "    * run tests automatically for each code commit, e.g. via GitLab-CI\n",
     "* Unit tests\n",
     "    * test functions, classes, modules individually\n",
     "* Integration tests\n",

notebooks/4a--Parallel_Programming.ipynb

@@ -121,12 +121,13 @@
     "\n",
     "#### How does Python fit in here?\n",
     "\n",
-    "* Level 1: distributed memory, communication via messages\n",
+    "* Level 1: distributed memory, communication via messages over a network\n",
     "    * `mpi4py`\n",
     "* Levels 2 and 3: shared memory\n",
+    "    * `mpi4py`\n",
     "    * `multiprocessing`\n",
     "    * threading, e.g. OpenMP, Cython, Numba, NumPy using an optimized math library like MKL\n",
-    "* Level 4: hope that the libraries (NumPy $\\to$ MKL) or compilers (C/F, Cython, Numba) do it right!"
+    "* Level 4: rely on libraries (NumPy $\\to$ MKL) or compilers (C/F, Cython, Numba) to do it right!"
    ]
   },
   {
@@ -257,7 +258,8 @@
    "source": [
     "## Parallelism in Python\n",
     "\n",
-    "* Threads (not useful for HPC)\n",
+    "* Python-internal threads (not useful for HPC!)\n",
+    "* multithreaded modules or libraries (e.g. Numba, NumPy with MKL, etc.)\n",
     "* Processes (shared memory)\n",
     "    * `multiprocessing`, comparably easy to use\n",
     "    * restricted to one node\n",
@@ -570,7 +572,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -595,7 +597,7 @@
     "p.start()\n",
     "print(q.get(), q.get(), q.get())\n",
     "p.join()\n",
-    "#print(q.get(), q.get(), q.get())"
+    "print(q.get(), q.get(), q.get())"
    ]
   },
   {
@@ -1883,8 +1885,8 @@
     "#SBATCH -e ./job.err.%j\n",
     "#SBATCH -D ./\n",
     "#SBATCH -J MPI4PY\n",
-    "#SBATCH --nodes=2             # launch 192 MPI tasks\n",
-    "#SBATCH --ntasks-per-node=96  #   on two full nodes (i.e. on 2 x 96 physical cores)\n",
+    "#SBATCH --nodes=2             # launch 144 MPI tasks\n",
+    "#SBATCH --ntasks-per-node=72  #   on two full nodes (i.e. on 2 x 72 physical cores)\n",
     "#SBATCH --cpus-per-task=1\n",
     "#SBATCH --time=00:10:00\n",
     "\n",
@@ -2223,7 +2225,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.3"
+   "version": "3.8.8"
   }
  },
  "nbformat": 4,