ipynb/john_stachurski-vectorization_numba.ipynb

{
    "cells": [
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## High Performance Python with Numba"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "#### John Stachurski"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Yes, the standard implementation of Python is slow, like other high level languages.\n",
                "\n",
                "But with Numba you can accelerate much of your scientific Python code to Fortran-like speeds with little effort.\n",
                "\n",
                "And then you can parallelize it and make it run even faster.\n",
                "\n",
                "In this notebook I'm going to discuss how this works.\n",
                "\n",
                "I'll begin by comparing two methods: vectorization and JIT compilation.\n",
                "\n",
                "By \"vectorization\" I mean working with arrays and matrices to speed up scientific computing. This is a neat trick that was pioneered by MATLAB.  The basic idea is that, with vectorized code, the overheads associated with running interpreted high level code are paid *per array* rather than per scalar operation.  With large arrays, that saves a lot of overhead.\n",
                "\n",
                "But vectorization is, in the end, a hack, and it has costs as well as benefits.  \n",
                "\n",
                "Fortunately, we have another alternative for accellerating code written in a high level language that is becoming increasing popular: just-in-time (JIT) compilation.  Even better, we have a JIT compiler for Python that's directly aimed at scientific computing and, while still young, developing rapidly into an extremely useful package.\n",
                "\n",
                "**TL;DR** Vectorization is neat but JIT compilation is better.  This notebook explores the key ideas using Python and Numba --- in my view the best package for modern scientific computing.\n",
                "\n"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 1,
            "metadata": {
                "nbpresent": {
                    "id": "cacd76f0-600a-4ac9-ba39-ae23747177c8"
                },
                "slideshow": {
                    "slide_type": "-"
                }
            },
            "outputs": [],
            "source": [
                "import numpy as np\n",
                "from numba import vectorize, jit, njit, float64, prange\n",
                "import matplotlib.pyplot as plt"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "### Vectorization"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "In scripting languages, native loops are slow:"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 2,
            "metadata": {},
            "outputs": [],
            "source": [
                "n = 1_000_000\n",
                "r_vec = np.random.randn(n)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 3,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "CPU times: user 113 ms, sys: 0 ns, total: 113 ms\n",
                        "Wall time: 115 ms\n"
                    ]
                }
            ],
            "source": [
                "%%time\n",
                "\n",
                "current_max = - np.Inf\n",
                "for x in r_vec:\n",
                "    if x > current_max:\n",
                "        current_max = x\n"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Python's built in `max` function is a little faster but not much:"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 4,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "CPU times: user 73.3 ms, sys: 0 ns, total: 73.3 ms\n",
                        "Wall time: 72.8 ms\n"
                    ]
                },
                {
                    "data": {
                        "text/plain": [
                            "4.928018945162083"
                        ]
                    },
                    "execution_count": 4,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "%%time\n",
                "\n",
                "max(r_vec)\n"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "The reason is that Python, like most high level languages is dynamically typed.\n",
                "\n",
                "This means that the type of a variable can change at any time.\n",
                "\n",
                "So the interpreter has to check the type of variables before any operation like addition, comparison, etc.\n",
                "\n",
                "Hence there's a lot of fixed cost for each such operation"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "The code runs much faster if we use **vectorized** expressions to avoid explicit loops."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 5,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "CPU times: user 0 ns, sys: 3.33 ms, total: 3.33 ms\n",
                        "Wall time: 855 µs\n"
                    ]
                },
                {
                    "data": {
                        "text/plain": [
                            "4.928018945162083"
                        ]
                    },
                    "execution_count": 5,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "%%time \n",
                "\n",
                "np.max(r_vec)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "It's the same if we use the equivalent method --- since we're calling into the same compiled code."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 6,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "CPU times: user 3.33 ms, sys: 0 ns, total: 3.33 ms\n",
                        "Wall time: 603 µs\n"
                    ]
                },
                {
                    "data": {
                        "text/plain": [
                            "4.928018945162083"
                        ]
                    },
                    "execution_count": 6,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "%%time\n",
                "\n",
                "r_vec.max()\n"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Now high level overheads are paid per *array* rather than per float or integer."
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Another example: To compute the sum of of $\\cos(2\\pi / x)$ over $x$ in "
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 7,
            "metadata": {},
            "outputs": [],
            "source": [
                "x_vec = np.linspace(0.1, 1.1, n)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "loops are slow..."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 8,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "CPU times: user 2.16 s, sys: 0 ns, total: 2.16 s\n",
                        "Wall time: 2.16 s\n"
                    ]
                }
            ],
            "source": [
                "%%time\n",
                "\n",
                "current_sum = 0.0\n",
                "for x in x_vec:\n",
                "    current_sum += np.cos(2 * np.pi / x)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "but vectorized code is fast:"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 9,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "CPU times: user 33.3 ms, sys: 3.33 ms, total: 36.7 ms\n",
                        "Wall time: 35.9 ms\n"
                    ]
                },
                {
                    "data": {
                        "text/plain": [
                            "135249.4192778737"
                        ]
                    },
                    "execution_count": 9,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "%%time\n",
                "\n",
                "np.sum(np.cos(2 * np.pi / x_vec))\n"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "#### Implict Multithreading"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Recent versions of Anaconda are compiled with Intel MKL support, which accelerates NumPy operations."
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Watch system resources when you run this code.  \n",
                "\n",
                "(For example, install `htop` (Linux / Mac), `perfmon` (Windows) or another system load monitor and set it running in another window.)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 10,
            "metadata": {},
            "outputs": [],
            "source": [
                "n = 20\n",
                "m = 1000\n",
                "for i in range(n):\n",
                "    X = np.random.randn(m, m)\n",
                "    λ = np.linalg.eigvals(X)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "You should see all your cores light up (but perhaps not all your \"CPUs\", depending on your hardware).  With MKL, many matrix operations are automatically parallelized."
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "### Problems with Vectorization"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Vectorization is neat but there are significant problems\n",
                "\n",
                "1. Loops are more flexible (some algorithms can't be vectorized)\n",
                "2. Memory intensive (see below)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "### Numba"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Recently something fun has come on the scene: fast, efficient just-in-time compilation within Python.  For numerical Python, the best JIT engine is Numba."
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Consider the time series model\n",
                "\n",
                "$$ x_{t+1} = \\alpha x_t (1 - x_t) $$\n",
                "\n",
                "Let's set $\\alpha = 4$"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 11,
            "metadata": {},
            "outputs": [],
            "source": [
                "α = 4.0"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Here's a typical time series:"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 12,
            "metadata": {},
            "outputs": [
                {
                    "data": {
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\n",
                        "text/plain": [
                            "<matplotlib.figure.Figure at 0x7f0cad04bbe0>"
                        ]
                    },
                    "metadata": {},
                    "output_type": "display_data"
                }
            ],
            "source": [
                "n = 200\n",
                "x =  np.empty(n)\n",
                "x[0] = 0.2\n",
                "for t in range(n-1):\n",
                "    x[t+1] = α * x[t] * (1 - x[t])\n",
                "    \n",
                "plt.plot(x)\n",
                "plt.show()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Here's a function that simulates for `n` periods, starting from `x0`, and returns **only the final** value:"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 13,
            "metadata": {},
            "outputs": [],
            "source": [
                "def quad(x0, n):\n",
                "    x = x0\n",
                "    for i in range(1, n):\n",
                "        x = α * x * (1 - x)\n",
                "    return x"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Let's see how fast this runs:"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 14,
            "metadata": {},
            "outputs": [],
            "source": [
                "n = 10_000_000"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 15,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "CPU times: user 947 ms, sys: 3.33 ms, total: 950 ms\n",
                        "Wall time: 950 ms\n"
                    ]
                }
            ],
            "source": [
                "%%time\n",
                "\n",
                "x = quad(0.2, n)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Now let's try this in FORTRAN.  In the following code, all parameters are the same as for the Python code above."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 16,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "Overwriting fastquad.f90\n"
                    ]
                }
            ],
            "source": [
                "%%file fastquad.f90\n",
                "\n",
                "PURE FUNCTION QUAD(X0, N)\n",
                " IMPLICIT NONE\n",
                " INTEGER, PARAMETER :: DP=KIND(0.d0)                           \n",
                " REAL(dp), INTENT(IN) :: X0\n",
                " REAL(dp) :: QUAD\n",
                " INTEGER :: I\n",
                " INTEGER, INTENT(IN) :: N\n",
                " QUAD = X0\n",
                " DO I = 1, N - 1                                                \n",
                "  QUAD = 4.0_dp * QUAD * real(1.0_dp - QUAD, dp)\n",
                " END DO\n",
                " RETURN\n",
                "END FUNCTION QUAD\n",
                "\n",
                "PROGRAM MAIN\n",
                " IMPLICIT NONE\n",
                " INTEGER, PARAMETER :: DP=KIND(0.d0)                          \n",
                " REAL(dp) :: START, FINISH, X, QUAD\n",
                " INTEGER :: N\n",
                " N = 10000000\n",
                " X = QUAD(0.2_dp, 10)\n",
                " CALL CPU_TIME(START)\n",
                " X = QUAD(0.2_dp, N)\n",
                " CALL CPU_TIME(FINISH)\n",
                " PRINT *,'last val = ', X\n",
                " PRINT *,'elapsed time = ', FINISH-START\n",
                "END PROGRAM MAIN"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "**Note** The next step will only execute if you have a FORTRAN compiler installed and modify the compilation code below appropriately.\n",
                "\n",
                "If you don't then skip execution of the next two cells --- you can just look at my numbers."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 17,
            "metadata": {},
            "outputs": [],
            "source": [
                "!gfortran -O3 fastquad.f90"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 18,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        " last val =   0.46200166384322749     \r\n",
                        " elapsed time =    5.9999999999999991E-002\r\n"
                    ]
                }
            ],
            "source": [
                "!./a.out"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Now let's do the same thing in Python using Numba's JIT compilation.  First we target the function for JIT compilation:"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 19,
            "metadata": {},
            "outputs": [],
            "source": [
                "quad_jitted = jit(quad)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Now let's call it:"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 20,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "CPU times: user 187 ms, sys: 20 ms, total: 207 ms\n",
                        "Wall time: 204 ms\n"
                    ]
                }
            ],
            "source": [
                "%%time\n",
                "\n",
                "x = quad_jitted(0.2, n)\n"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 21,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "CPU times: user 30 ms, sys: 0 ns, total: 30 ms\n",
                        "Wall time: 29.6 ms\n"
                    ]
                }
            ],
            "source": [
                "%%time\n",
                "\n",
                "x = quad_jitted(0.2, n)\n"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "After JIT compilation, function execution speed is about the same as Fortran.\n",
                "\n",
                "Thus, in the sense of serial execution, it's running as fast as it can go.\n",
                "\n",
                "The second call is faster than the first because there's no hold up for compilation --- the compiled instructions now live in RAM and, in the second instance, the call is dispatched to this precompiled code.\n",
                "\n",
                "Note, however, that if you were to call the function with arguments such that their types are no longer the same as the types of the previous calls, then the compiler will generate a new set of machine code, and store it in memory along with the first.  Subsequent calls will be dispatched to the right code by Numba."
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "#### Decorator Syntax"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "By the way, a more common way to target a function for JIT compilation is to use a decorator, like so:"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 22,
            "metadata": {},
            "outputs": [],
            "source": [
                "@jit\n",
                "def f(x):\n",
                "    return 2 * x"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "You can also use `@njit` or, equivalently, `@jit(nopython=True)` to force an error if the JIT compiler is unable to compile your code efficiently (in particular, if it has to fall back to object mode):"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 23,
            "metadata": {},
            "outputs": [],
            "source": [
                "@njit\n",
                "def f(x):\n",
                "    return 2 * x"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "#### How does it work?"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "The secret sauce is type inference inside the function body.\n",
                "\n",
                "When we call `quad_jitted` with particular arguments, Numba's compiler works through the function body and infers the types of the variables inside the function.\n",
                "\n",
                "It then produces compiled code *specialized to that type signature*\n",
                "\n",
                "For example, we called `quad_jitted` with a `float, int` pair in the cell above and the compiler produced code specialized to those types.\n",
                "\n",
                "That code runs fast because the compiler can fully specialize all operations inside the function based on that information and hence write very efficient machine code."
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "#### Limitations of Numba"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 24,
            "metadata": {},
            "outputs": [],
            "source": [
                "from scipy.integrate import quad\n",
                "\n",
                "\n",
                "def compute_integral(n):\n",
                "    return quad(lambda x: x**(1/n), 0, 1)\n",
                "        "
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 25,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "(0.8000000000000004, 8.881784197001256e-16)"
                        ]
                    },
                    "execution_count": 25,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "compute_integral(4)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 26,
            "metadata": {},
            "outputs": [],
            "source": [
                "@jit\n",
                "def compute_integral(n):\n",
                "    return quad(lambda x: x**(1/n), 0, 1)\n",
                "        "
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "If you uncomment and run the next line you'll get an error."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 27,
            "metadata": {},
            "outputs": [],
            "source": [
                "#compute_integral(4)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "The reason is that the `quad` function is from SciPy and Numba doesn't know how to handle it.\n",
                "\n",
                "This is the biggest problem with Numba.  A large suit of scientific tools aren't currently compatible.\n",
                "\n",
                "On the other hand, it's a problem that people are well aware of, and various people are racing to overcome.\n",
                "\n",
                "Second, even though it might not be possible to JIT-compile your whole program, you might well be able to compile the hot loops that are eating up 99% of your computation time.\n",
                "\n",
                "If you can do this, you open up large speed gains, as the following sections make clear."
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "### Vectorization vs Numba"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "The problem is to maximize the function \n",
                "\n",
                "$$ f(x, y) = \\frac{\\cos \\left(x^2 + y^2 \\right)}{1 + x^2 + y^2} + 1$$\n",
                "\n",
                "using brute force --- searching over a grid of $(x, y)$ pairs."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 28,
            "metadata": {},
            "outputs": [],
            "source": [
                "def f(x, y):\n",
                "    return np.cos(x**2 + y**2) / (1 + x**2 + y**2) + 1"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 29,
            "metadata": {
                "scrolled": false
            },
            "outputs": [
                {
                    "data": {
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\n",
                        "text/plain": [
                            "<matplotlib.figure.Figure at 0x7f0ca003feb8>"
                        ]
                    },
                    "metadata": {},
                    "output_type": "display_data"
                }
            ],
            "source": [
                "from mpl_toolkits.mplot3d.axes3d import Axes3D\n",
                "from matplotlib import cm\n",
                "\n",
                "gridsize = 50\n",
                "gmin, gmax = -3, 3\n",
                "xgrid = np.linspace(gmin, gmax, gridsize)\n",
                "ygrid = xgrid\n",
                "x, y = np.meshgrid(xgrid, ygrid)\n",
                "\n",
                "# === plot value function === #\n",
                "fig = plt.figure(figsize=(10, 8))\n",
                "ax = fig.add_subplot(111, projection='3d')\n",
                "ax.plot_surface(x,\n",
                "                y,\n",
                "                f(x, y),\n",
                "                rstride=2, cstride=2,\n",
                "                cmap=cm.jet,\n",
                "                alpha=0.4,\n",
                "                linewidth=0.05)\n",
                "\n",
                "\n",
                "ax.scatter(x, y, c='k', s=0.6)\n",
                "\n",
                "ax.scatter(x, y, f(x, y), c='k', s=0.6)\n",
                "\n",
                "ax.view_init(25, -57)\n",
                "ax.set_zlim(-0, 2.0)\n",
                "ax.set_xlim(gmin, gmax)\n",
                "ax.set_ylim(gmin, gmax)\n",
                "\n",
                "plt.show()\n"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "#### Vectorized code"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Let's see how fast the vectorized approach runs."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 30,
            "metadata": {},
            "outputs": [],
            "source": [
                "grid = np.linspace(-3, 3, 10_000)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 31,
            "metadata": {},
            "outputs": [],
            "source": [
                "x, y = np.meshgrid(grid, grid)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 32,
            "metadata": {
                "nbpresent": {
                    "id": "1ba9f9f9-f737-4ee1-86e6-0a33c4752188"
                }
            },
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "CPU times: user 2.89 s, sys: 187 ms, total: 3.08 s\n",
                        "Wall time: 3.08 s\n"
                    ]
                },
                {
                    "data": {
                        "text/plain": [
                            "1.999999819964011"
                        ]
                    },
                    "execution_count": 32,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "%%time \n",
                "np.max(f(x, y))\n"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "#### JITTed code"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "A jitted version"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 33,
            "metadata": {},
            "outputs": [],
            "source": [
                "@jit\n",
                "def compute_max():\n",
                "    m = -np.inf\n",
                "    for x in grid:\n",
                "        for y in grid:\n",
                "            z = np.cos(x**2 + y**2) / (1 + x**2 + y**2) + 1\n",
                "            if z > m:\n",
                "                m = z\n",
                "    return m"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 34,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "CPU times: user 2.16 s, sys: 6.67 ms, total: 2.17 s\n",
                        "Wall time: 2.16 s\n"
                    ]
                },
                {
                    "data": {
                        "text/plain": [
                            "1.999999819964011"
                        ]
                    },
                    "execution_count": 34,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "%%time\n",
                "\n",
                "compute_max()\n"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 35,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "CPU times: user 2.11 s, sys: 0 ns, total: 2.11 s\n",
                        "Wall time: 2.1 s\n"
                    ]
                },
                {
                    "data": {
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                            "1.999999819964011"
                        ]
                    },
                    "execution_count": 35,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "%%time\n",
                "\n",
                "compute_max()\n"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "This is faster than the vectorized code.  In both cases we have highly specialized and optimized machine code.  However, the vectorized code is much more memory intensive because it generates a lot of intermediate arrays, all of which are large.  \n",
                "\n",
                "That's why it's relatively slow.  This is a common problem with vectorized code in computationally intensive settings."
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "#### JITTed, parallelized code: @vectorize"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {
                "nbpresent": {
                    "id": "3de27362-4528-4669-8e3d-2e7db1dd0721"
                }
            },
            "source": [
                "For this particular example, Numba plus vectorization with automatic parallization is even faster:"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 36,
            "metadata": {
                "nbpresent": {
                    "id": "e443f7ad-f26e-4148-983e-83a5f6a2214e"
                }
            },
            "outputs": [],
            "source": [
                "@vectorize('float64(float64, float64)', target='parallel')\n",
                "def f_par(x, y):\n",
                "    return np.cos(x**2 + y**2) / (1 + x**2 + y**2) + 1"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 37,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "1.999999819964011"
                        ]
                    },
                    "execution_count": 37,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "x, y = np.meshgrid(grid, grid)\n",
                "\n",
                "np.max(f_par(x, y))"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 38,
            "metadata": {
                "nbpresent": {
                    "id": "08ff9d10-b80e-489f-8e7e-5e1869903393"
                }
            },
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "CPU times: user 3.54 s, sys: 46.7 ms, total: 3.59 s\n",
                        "Wall time: 514 ms\n"
                    ]
                },
                {
                    "data": {
                        "text/plain": [
                            "1.999999819964011"
                        ]
                    },
                    "execution_count": 38,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "%%time\n",
                "\n",
                "np.max(f_par(x, y))"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "### Summary"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "We just scratched the surface of Numba goodness.  For further reading see:\n",
                "    \n",
                "* [the docs](http://numba.pydata.org/)\n",
                "* [this overview](http://matthewrocklin.com/blog/work/2018/01/30/the-case-for-numba)"
            ]
        }
    ],
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