Jacobi stencil

License

Copyright 2024 NVIDIA Corporation

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
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     http://www.apache.org/licenses/LICENSE-2.0

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distributed under the License is distributed on an "AS IS" BASIS,
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To get started, import cunumeric as np (just the same way we would import numpy)

import cunumeric as np  # instead of numpy

# Because of Legate's deferred execution model, legate.timing should be used instead
# of standard Python datetime utilities. Python datetime.now would return the time
# a task is *scheduled*, not necessarily the time a task finishes executing.
from legate.timing import time

def jacobi(grid, I):
    print("Running Jacobi stencil... ", end="")

    center = grid[1:-1, 1:-1]
    north = grid[0:-2, 1:-1]
    east = grid[1:-1, 2:]
    west = grid[1:-1, 0:-2]
    south = grid[2:, 1:-1]

    start = time()
    for i in range(I):
        average = center + north + east + west + south
        center[:] = 0.2 * average
    stop = time()

    print(f"Elapsed Time: {(stop - start)/1000} ms")

    return grid

We also want to define a small helper function make_grid to generate a test grid for us to use

def make_grid(N):
    grid = np.zeros((N + 2, N + 2))
    grid[:, 0] = -273.15
    grid[:, -1] = -273.15
    grid[-1, :] = -273.15
    grid[0, :] = 40.0
    return grid

Let’s first create a grid using make_grid, and see what it looks like using Matplotlib’s pcolor function

import matplotlib.pyplot as plt

G = make_grid(100)

plt.pcolor(G);

As we can see it produces a two dimensional array of zeros with some different values on the boundaries. Now let’s run 1000 iterations of our Jacobi stencil on this image and look at the result.

G = jacobi(G, 1000)

plt.pcolor(G);

Running Jacobi stencil... Elapsed Time: 2461.875 ms

We can see that the effect of running the stencil over the image repeatedly is to average out all the pixels.