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Example of CPU vs GPU for image convolution - demonstrates CPU vs GPU - Created while evaluating NVidia AI Workbench
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{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"id": "519f074d-cc80-401d-ae17-d87babd5230c", | |
"metadata": {}, | |
"source": [ | |
"# Convolution\n", | |
"Source [this medium article](https://medium.com/@geminae.stellae/introduction-to-gpu-programming-with-python-cuda-577bfdaa47f3)\n", | |
"\n", | |
"## Create the dataset\n" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 34, | |
"id": "35c0393c-a74e-4519-ac38-6c7e24b5d9d2", | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"import numpy as np\n", | |
"\n", | |
"# Construct an image with repeated delta functions\n", | |
"deltas = np.zeros((4096, 4096))\n", | |
"# starting at 8 and 16 apart in each direction\n", | |
"deltas[8::16,8::16] = 1" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "b5337a27-e8b8-4b93-be6d-f20655c76a2b", | |
"metadata": {}, | |
"source": [ | |
"# Visualization\n", | |
"\n", | |
"## Visualizing our source image" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 35, | |
"id": "513ae9be-2192-472e-9cb3-d7174fa102ce", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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", | |
"text/plain": [ | |
"<Figure size 640x480 with 1 Axes>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"import pylab as pyl\n", | |
"# Necessary command to render a matplotlib image in a Jupyter notebook.\n", | |
"%matplotlib inline\n", | |
"\n", | |
"# Display the image\n", | |
"pyl.imshow(deltas[0:100, 0:100])\n", | |
"pyl.show()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "6c8e45b9-6bc3-44e3-b080-02e0638f3673", | |
"metadata": {}, | |
"source": [ | |
"convolve our image with a Bicubic interpolation" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "f247c6a9-d3fd-49a6-9867-22b66da1a54f", | |
"metadata": {}, | |
"source": [ | |
"## Demonstrate the convolution effect on a single square" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 40, | |
"id": "5926090e-1d15-4c43-9366-977d734e5721", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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", | |
"text/plain": [ | |
"<Figure size 640x480 with 1 Axes>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"import pylab as pyl\n", | |
"# doing this on the CPU -- not timing it\n", | |
"x, y = np.meshgrid(np.linspace(-2, 2, 15), np.linspace(-2, 2, 15))\n", | |
"dst = np.sqrt(x*x + y*y)\n", | |
"sigma = 1\n", | |
"muu = 0.000\n", | |
"pyl.imshow(dst,interpolation='bicubic')\n", | |
"pyl.show()\n" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "f22c2579-0bf1-4893-aad2-e68cfd4f5426", | |
"metadata": {}, | |
"source": [ | |
"## Demonstrate convolution effect on data set" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 37, | |
"id": "82cca88b-297f-48f7-8692-c48f4a6e4aa4", | |
"metadata": { | |
"scrolled": true | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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", | |
"text/plain": [ | |
"<Figure size 640x480 with 1 Axes>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"from scipy.signal import convolve2d as convolve2d_cpu\n", | |
"# run convolution on CPU and show plot\n", | |
"convolved_image_using_CPU = convolve2d_cpu(deltas, dst)\n", | |
"pyl.imshow(convolved_image_using_CPU[0:100, 0:100])\n", | |
"pyl.show()\n" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "fc444c87-4b17-4238-9567-a194d8715417", | |
"metadata": {}, | |
"source": [ | |
"# Time Convolution on the CPU using scipy\n", | |
"# Time Convolution on CPU" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 38, | |
"id": "9a69c0b4-2701-46c1-9640-dd4117c0b5a9", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"5.73 s ± 0 ns per loop (mean ± std. dev. of 1 run, 1 loop each)\n" | |
] | |
} | |
], | |
"source": [ | |
"# run convolution on CPU and time it without plot for timer comparison\n", | |
"from scipy.signal import convolve2d as convolve2d_cpu\n", | |
"%timeit -n 1 -r 1 convolve2d_cpu(deltas, dst)" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "970d1512-16be-4501-aa03-26e9e071195e", | |
"metadata": {}, | |
"source": [ | |
"# Convolution on GPU using cupy\n", | |
"\n", | |
"## Time convolution on the GPU" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 39, | |
"id": "a1bbf68e-8088-461b-b64c-a77153d35651", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"97.8 ms ± 0 ns per loop (mean ± std. dev. of 1 run, 7 loops each)\n" | |
] | |
} | |
], | |
"source": [ | |
"# Copy to GPU\n", | |
"import cupy as cp\n", | |
"from cupyx.scipy.signal import convolve2d as convolve2d_gpu\n", | |
"\n", | |
"def transfer_to_gpu_compute_transfer_to_cpu():\n", | |
" # copy the data to GPU memory\n", | |
" deltas_gpu = cp.asarray(deltas)\n", | |
" dst_gpu = cp.asarray(dst)\n", | |
" # execute convolution\n", | |
" convolved_image_using_GPU = convolve2d_gpu(deltas_gpu, dst_gpu)\n", | |
" # Copy the data back to the CPU\n", | |
" # So we can compare timings after the data lands in the same place for both\n", | |
" convolved_image_using_GPU_copied_to_host = cp.asnumpy(convolved_image_using_GPU)\n", | |
" return convolved_image_using_GPU_copied_to_host\n", | |
"\n", | |
"%timeit -n 7 -r 1 transfer_to_gpu_compute_transfer_to_cpu()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"id": "b05a2e1f-0358-4f6c-aac8-5817152b7b24", | |
"metadata": {}, | |
"outputs": [], | |
"source": [] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 3 (ipykernel)", | |
"language": "python", | |
"name": "python3" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.10.12" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 5 | |
} |
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