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Merge pull request #303 from chaoming0625/parallel_doc
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update doc
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@chaoming0625
chaoming0625 authored Nov 25, 2022
2 parents 68bfc36 + de997ae commit 4c3433d
Showing 1 changed file with 46 additions and 48 deletions.
94 changes: 46 additions & 48 deletions docs/tutorial_simulation/parallel_computing.ipynb
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"current = bm.linspace(1, 10.1, 10) # here only one parameter"
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Expand All @@ -198,14 +198,14 @@
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"def hh_spike_num2(bg_current): # \"input\" is the bg_current\n",
" import brainpy as bp # needed to reimport packages when\n",
" # run the function in Jupyter\n",
"\n",
" bg_current = bm.as_jax(bg_current)\n",
" bg_current = bp.math.as_jax(bg_current)\n",
" model = bp.neurons.HH(1)\n",
" runner = bp.dyn.DSRunner(model, monitors=['spike'], inputs=['input', bg_current])\n",
" runner.run(1000.)\n",
Expand All @@ -228,25 +228,25 @@
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Expand All @@ -261,6 +261,15 @@
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"If you think that the order of the running results does not matter, you can also use ``cpu_unordered_parallel()`` function. This can maximize the running efficiency of all processors, since all workers run with a non-blocking and unordered manner."
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"def hh_spike_num3(bg_current): # \"input\" is the bg_current\n",
Expand All @@ -329,15 +338,15 @@
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"source": [
"bp.math.set_host_device_count(10)\n",
"bp.math.set_host_device_count(10) # this should place on the top of the file\n",
"current = bm.linspace(1., 10.1, 20)\n",
"r = bp.running.jax_vectorize_map(hh_spike_num3, [current], num_parallel=10, clear_buffer=True)\n",
"r = bp.running.jax_parallelize_map(hh_spike_num3, [current], num_parallel=10, clear_buffer=True)\n",
"r"
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Expand All @@ -587,10 +584,10 @@
}
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"```python\n",
"\n",
"#!/bin/bash\n",
"#SBATCH -J <name>\n",
"#SBATCH -o <file name>\n",
Expand All @@ -599,7 +596,8 @@
"#SBATCH -N <int>\n",
"#SBATCH -c <int>\n",
"\n",
"python your_script.py"
"python your_script.py\n",
"```"
],
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"collapsed": false
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