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docs/Documentation.ipynb

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"Profiling is performed using the `submit.sh` file in the `shell` folder, which internally \n",
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"We begin by discussing the memory consumption of the method, studying how it varies with respect to the matrix size and number of processes, and comparing it to `numpy`'s and `scipy`'s `eig` built-in function.\n",
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"\n",
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"*IMPORTANT*: please notice that we did not use `scipy.sparse`'s solver as it cannot be used to retrieve all the eigenvalues, which would have make the comparison unfair.\n",
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"\n",
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"![Memory profiling](plots/memory_profiling.png)\n",
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"\n",
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"It is possible to see that cumulative memory consumption does not really depend on the number of processes, and that for low values of $n$ it behaves better than `numpy` and `scipy`, while performance degradates for high values of $n$.\n",

experiments/config.yaml

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dim: 200
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dim: 500
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density: 0.1
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n_processes: 2
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plot: false

shell/submit.sh

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#!/bin/bash
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# Ranges over which we iterate
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n_processes=(2 4 8)
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n_processes=(1 2 4 8)
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matrix_sizes=(10 50 100 500 1000 1500)
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last_dim="${matrix_sizes[-1]}"

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