Add IO bounded in parallel

ipynb/40_parallel.ipynb

@@ -40,6 +40,53 @@
     "- IO bounded (wait for IO)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Different parallel strategies"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "-"
+    }
+   },
+   "source": [
+    "### IO bounded: one process + `async`/`await`\n",
+    "\n",
+    "<p class=\"small\"><br></p>\n",
+    "\n",
+    "Cooperative concurrency\n",
+    "\n",
+    "<p class=\"small\"><br></p>\n",
+    "\n",
+    "Functions able to pause\n",
+    "\n",
+    "<p class=\"small\"><br></p>\n",
+    "\n",
+    "`asyncio`, [`trio`](https://trio.readthedocs.io)"
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "-"
+    }
+   },
+   "source": [
+    "<div align=\"middle\">\n",
+    "<img src=\"./fig/logo_trio.png\"  style=\"width: 15%\">\n",
+    "</div>"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -164,7 +211,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.2"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,
 %% Cell type:markdown id: tags:
 
 # Parallel computing (CPU bounded)
 
 Pierre Augier (LEGI), Cyrille Bonamy (LEGI), Eric Maldonado (Irstea), Franck Thollard (ISTerre), Christophe Picard (LJK), Loïc Huder (ISTerre)
 
 %% Cell type:markdown id: tags:
 
 # Parallelism
 
 ## Hardware:
 
 - Multicore CPU
 
 - Multi nodes super computers (MPI)
 
 - GPU (Nvidia: Cuda, Cupy) / Intel Xeon Phi
 
 <p class="small"><br></p>
 
 ## Different problems
 
 - CPU bounded (need to use cores at the same time)
 
 - IO bounded (wait for IO)
 
 %% Cell type:markdown id: tags:
 
 ## Different parallel strategies
 
+%% Cell type:markdown id: tags:
+
+### IO bounded: one process + `async`/`await`
+
+<p class="small"><br></p>
+
+Cooperative concurrency
+
+<p class="small"><br></p>
+
+Functions able to pause
+
+<p class="small"><br></p>
+
+`asyncio`, [`trio`](https://trio.readthedocs.io)
+
+%% Cell type:raw id: tags:
+
+<div align="middle">
+<img src="./fig/logo_trio.png"  style="width: 15%">
+</div>
+
+%% Cell type:markdown id: tags:
+
+## Different parallel strategies
+
 ### One process split in light subprocesses called threads 👩🏼‍🔧 👨🏼‍🔧👩🏼‍🔧 👨🏼‍🔧
 
 - handled by the OS
 
 - share memory and can use at the same time different CPU cores
 
 How?
 
 - OpenMP (Natively in C / C++ / Fortran. For Python: Pythran, Cython, ...)
 
 - In Python: `threading` and `concurrent.futures`
 
 %% Cell type:markdown id: tags:
 
 **⚠️ in Python, one interpreter per process (~) and the Global Interpreter Lock (GIL)...**
 
 - In a Python program, different threads can run at the same time (and take advantage of multicore)
 
 - But... the Python interpreter runs the Python bytecodes sequentially !
 
     - *Terrible* 🐌 for CPU bounded *if the Python interpreter is used a lot* !
 
     - *No problem* for IO bounded !
 
     - *No problem* for extensions when the interpreter is not used !
 
 %% Cell type:markdown id: tags:
 
 ## Different parallel strategies
 
 ### One program, $n$ processes 👩🏼‍🔧 👨🏼‍🔧👩🏼‍🔧 👨🏼‍🔧
 
 ### Exchange data:
 
 Very efficient and no problem with Python!
 
 - With MPI: mpi4py and h5py parallel
 
 - multiprocessing
 
 - [ZeroMQ](http://zeromq.org/)
 
 %% Cell type:markdown id: tags:
 
 ## Other packages for parallel computing with Python
 
 - IPython
 - dask
 - joblib
 
 %% Cell type:markdown id: tags:
 
 # Code examples
 
 ## Target algorithms :
 
   - computes the first prime number (with a **very** brute force algorithm)
   - given a set of number, computes the distance map between each number
   - computes for a set of number, its factors
 
 ## Solutions
 
 - multiprocessing (map)
 - multiprocessing (starmap)
 - concurent.futures
 - ...