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ma-sadeghi/TestPardiso4py.ipynb

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Test pardiso4py's performance against scipy/umfpack's spsolve
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TestPardiso4py.ipynb
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"cells": [
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"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Nx: 9 Solver: pypardiso.spsolve Runtime (s): 0.03 \n",
"Nx: 9 Solver: scipy.spsolve Runtime (s): 0.01 \n",
"Nx: 9 Solver: scipy.cg Runtime (s): 0.01 \n",
"----------------------------------------\n",
"Nx: 14 Solver: pypardiso.spsolve Runtime (s): 0.03 \n",
"Nx: 14 Solver: scipy.spsolve Runtime (s): 0.04 \n",
"Nx: 14 Solver: scipy.cg Runtime (s): 0.02 \n",
"----------------------------------------\n",
"Nx: 17 Solver: pypardiso.spsolve Runtime (s): 0.05 \n",
"Nx: 17 Solver: scipy.spsolve Runtime (s): 0.09 \n",
"Nx: 17 Solver: scipy.cg Runtime (s): 0.03 \n",
"----------------------------------------\n",
"Nx: 19 Solver: pypardiso.spsolve Runtime (s): 0.07 \n",
"Nx: 19 Solver: scipy.spsolve Runtime (s): 0.13 \n",
"Nx: 19 Solver: scipy.cg Runtime (s): 0.04 \n",
"----------------------------------------\n",
"Nx: 21 Solver: pypardiso.spsolve Runtime (s): 0.09 \n",
"Nx: 21 Solver: scipy.spsolve Runtime (s): 0.19 \n",
"Nx: 21 Solver: scipy.cg Runtime (s): 0.05 \n",
"----------------------------------------\n"
]
}
],
"source": [
"import numpy as np\n",
"import openpnm as op\n",
"from openpnm.utils import tic, toc\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib as mpl\n",
"%matplotlib inline\n",
"%config InlineBackend.figure_format = 'svg'\n",
"\n",
"solvers = [\"pypardiso.spsolve\", \"scipy.spsolve\", \"scipy.cg\"]\n",
"runtime = {solver: [] for solver in solvers}\n",
"num_pores = np.linspace(1000, 10_000, 5)\n",
"num_repeat = 3\n",
"\n",
"for nx in (num_pores**(1/3)).astype(int):\n",
" num_repeat = 1 if nx**3 > 30_000 else num_repeat\n",
" net = op.network.Cubic(shape=[nx] * 3)\n",
" geom = op.geometry.GenericGeometry(network=net, pores=net.Ps, throats=net.Ts)\n",
" phase = op.phases.GenericPhase(network=net)\n",
" phys = op.physics.GenericPhysics(network=net, geometry=geom, phase=phase)\n",
"\n",
" fd = op.algorithms.FickianDiffusion(network=net, phase=phase)\n",
" fd.set_value_BC(pores=net.pores(\"left\"), values=1.0)\n",
" fd.set_value_BC(pores=net.pores(\"right\"), values=0.1)\n",
" fd.settings[\"cache_A\"] = False\n",
" fd.settings[\"cache_b\"] = False\n",
" \n",
" for solver in solvers:\n",
" solver_family, solver_type = solver.split(\".\")\n",
" fd.set_solver(solver_family=solver_family, solver_type=solver_type) \n",
" \n",
" temp = []\n",
" for repeat in range(num_repeat):\n",
" phys[\"throat.diffusive_conductance\"] = np.random.rand()\n",
"\n",
" tic()\n",
" fd.run()\n",
" dt = toc(quiet=True)\n",
" temp.append(dt)\n",
" \n",
" runtime[solver].append(np.mean(temp))\n",
" print(f\"Nx: {nx:<5} Solver: {solver:<20} Runtime (s): {np.mean(temp):<10.2f}\")\n",
" print(\"-\" * 40)\n",
"\n",
"for solver in solvers:\n",
" runtime[solver] = np.array(runtime[solver])\n",
"\n",
"speedup_pypardiso_scipy = runtime[\"scipy.spsolve\"] / runtime[\"pypardiso.spsolve\"]\n",
"speedup_pypardiso_cg = runtime[\"scipy.cg\"] / runtime[\"pypardiso.spsolve\"]"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
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"source": [
"fig, ax = plt.subplots()\n",
"ax.plot(num_pores, speedup_pypardiso_scipy, \"o-\", label=\"vs. spsolve.spsolve\");\n",
"# ax.plot(num_pores, speedup_pypardiso_cg, \"^--\", label=\"vs. spsolve.cg\");\n",
"ax.set_xlabel(\"Total number of pores\");\n",
"ax.set_ylabel(\"Speedup\");\n",
"ax.legend()\n",
"ax.set_title(\"PyPardiso vs. Scipy Solvers\");\n",
"# ax.get_xaxis().set_major_formatter(\n",
"# mpl.ticker.FuncFormatter(lambda x, p: format(int(x), ','))\n",
"# )\n",
"plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))"
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}
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