From b3521c23cd3e650098f48f8d8b5e56cf56a80bff Mon Sep 17 00:00:00 2001
From: Brent Huisman <brenthuisman@users.noreply.github.com>
Date: Wed, 8 Jun 2022 10:04:33 +0200
Subject: [PATCH] Tutorial uses all logical cores
Add tutorial on using all logical cores on a machine, facilitated by the new flag to context creation.
---
doc/tutorial/network_ring.rst | 10 ++++++++--
doc/tutorial/network_ring_mpi.rst | 4 ++++
python/example/brunel.py | 2 +-
python/example/network_ring.py | 5 ++---
4 files changed, 15 insertions(+), 6 deletions(-)
diff --git a/doc/tutorial/network_ring.rst b/doc/tutorial/network_ring.rst
index 84535f5a..7a70fe65 100644
--- a/doc/tutorial/network_ring.rst
+++ b/doc/tutorial/network_ring.rst
@@ -114,8 +114,14 @@ The execution
To create a simulation, we must create an :class:`arbor.context` and :py:class:`arbor.domain_decomposition`.
-Step **(12)** creates a default execution context, and uses the :func:`arbor.partition_load_balance` to create a
-default domain decomposition. You can print the objects to see what defaults they produce on your system.
+Step **(12)** initalizes the ``threads`` parameter of :class:`arbor.context` with the ``avail_threads`` flag. By supplying
+this flag, a context is constructed that will use all locally available threads. On your local machine this will match the
+number of logical cores in your system. Especially with large numbers
+of cells you will notice the speed-up. (You could instantiate the recipe with 5000 cells and observe the difference. Don't
+forget to turn of plotting if you do; it will take more time to generate the image then to run the actual simulation!)
+:func:`arbor.partition_load_balance` creates a default domain decomposition, which
+for contexts initialized with ``threads=avail_threads`` distributes cells evenly over the available cores. You can print the
+objects to see what defaults they produce on your system.
Step **(13)** sets all spike generators to record using the :py:class:`arbor.spike_recording.all` policy.
This means the timestamps of the generated events will be kept in memory. Be default, these are discarded.
diff --git a/doc/tutorial/network_ring_mpi.rst b/doc/tutorial/network_ring_mpi.rst
index e915c9df..e629113e 100644
--- a/doc/tutorial/network_ring_mpi.rst
+++ b/doc/tutorial/network_ring_mpi.rst
@@ -26,6 +26,10 @@ Step **(11)** is changed to generate a network with five hundred cells.
The hardware context
********************
+The configuration of the :py:class:`arbor.context` will need to be changed to reflect the change in hardware.
+First of all, we scrap setting `threads="avail_threads"` and instead use
+`MPI <https://en.wikipedia.org/wiki/Message_Passing_Interface#Overview>`_ to distribute the work over nodes, cores and threads.
+
Step **(12)** uses the Arbor-built-in :py:class:`MPI communicator <arbor.mpi_comm>`, which is identical to the
``MPI_COMM_WORLD`` communicator you'll know if you are familiar with MPI. The :py:class:`arbor.context` takes a
communicator for its ``mpi`` parameter. Note that you can also pass in communicators created with ``mpi4py``.
diff --git a/python/example/brunel.py b/python/example/brunel.py
index 541a72c4..944916ed 100755
--- a/python/example/brunel.py
+++ b/python/example/brunel.py
@@ -117,7 +117,7 @@ if __name__ == "__main__":
for k,v in vars(opt).items():
print(f"{k} = {v}")
- context = arbor.context()
+ context = arbor.context("avail_threads")
print(context)
meters = arbor.meter_manager()
diff --git a/python/example/network_ring.py b/python/example/network_ring.py
index 953b31b1..0ae49f5d 100755
--- a/python/example/network_ring.py
+++ b/python/example/network_ring.py
@@ -108,8 +108,8 @@ class ring_recipe (arbor.recipe):
ncells = 4
recipe = ring_recipe(ncells)
-# (12) Create a default execution context, domain decomposition and simulation
-context = arbor.context()
+# (12) Create an execution context using all locally available threads, domain decomposition and simulation
+context = arbor.context("avail_threads")
decomp = arbor.partition_load_balance(recipe, context)
sim = arbor.simulation(recipe, decomp, context)
@@ -120,7 +120,6 @@ sim.record(arbor.spike_recording.all)
handles = [sim.sample((gid, 0), arbor.regular_schedule(0.1)) for gid in range(ncells)]
# (15) Run simulation for 100 ms
-sim.progress_banner()
sim.run(100)
print('Simulation finished')
--
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