Hello everyone,

I wasn't quite sure if I should post the issue here or on the PACMAN repo instead and therefore sorry if I misplaced that one.

Setup description

I have a workflow which creates a network of arbitrary size but with a fixed topology whose interconnected populations of neurons (targets) are also connected to SpikeSourceArray input populations (sources). The targets have been set to stream their output in real-time.

Problem

The workflow fails during partitioning graph vertices with the following (abbreviated) error message:

Partitioning graph vertices
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2017-07-17 15:51:29 ERROR: Error when calling pacman.operations.partition_algorithms.partition_and_place_partitioner.PartitionAndPlacePartitioner.call with inputs {'machine': [Machine: max_x=23, max_y=11, chips=[[Chip: x=0, y=0, sdram=117 MB, ip_address=192.168.2.1, router=[Router: clock_speed=157 MHz, emergency_routing=False,available_entries=1023, links=[[Link: source_x=0, source_y=0, source_link_id=0, destination_x=1, destination_y=0, default_from=3, default_to=3], [Link: source_x=0, source_y=0, source_link_id=1, destination_x=1, destination_y=1, default_from=4, default_to=4], [Link: source_x=0, source_y=0, source_link_id=2, destination_x=0, destination_y=1, default_from=5, default_to=5], [Link: source_x=0, source_y=0, source_link_id=3, destination_x=23, destination_y=0, default_from=0, default_to=0], [Link: source_x=0, source_y=0, source_link_id=4, destination_x=23, destination_y=11, default_from=1, default_to=1], [Link: source_x=0, source_y=0, source_link_id=5, destination_x=0, destination_y=11, default_from=2, default_to=2]]], processors=[[CPU: id=0, clock_speed=200 MHz, monitor=True], [.......] [CPU: id=17, clock_speed=200 MHz, monitor=False]], nearest_ethernet=16:8]]], 'graph': <pacman.model.graphs.application.application_graph.ApplicationGraph object at 0x7f79ee7c27a0>, 'preallocated_resources': <pacman.model.resources.pre_allocated_resource_container.PreAllocatedResourceContainer object at 0x7f79ec2af200>}

It is important to mention that the failing program runs successfully when using a sPyNNaker release from September 2016 instead of sPyNNaker7.
I also tried to reproduce the error in a separate minimalistic script using a single source and target neurons but it ran just well. So it must be something in the network's topology that breaks it, I assume. However when I down-scaled my SNN such that only 32 populations are created (preserving the original topology) the PartitionAndPlacePartitioner completed without any exception. Then I tried it slightly larger (36 populations) and it failed with the aforementioned error message.

Do you have any idea what might be causing that? A spynnaker.cfg issue? Or maybe I miss something when porting my sPyNNaker Sept 2016 code to sPyNNaker7? The only thing I have changed are some import statements:

1. from import spynnaker.pyNN to spynnaker7.pyNN
2. and also one broken old import: from import spynnaker_external_devices_plugin.pyNN as external_device to from spynnaker_external_devices_plugin.pyNN import SpynnakerExternalDevicePluginManager so that SpynnakerExternalDevicePluginManager .activate_live_output_for(...) can be applied on the targets.

Interestingly, the code ran without exceptions some two weeks ago but started to fail after I reinstalled the SpiNNaker tool chain on the 10.07.2017. I will try to revert to a previous commit and check whether it is any more successful. I will also try to compose a fairly small script reproducing this issue if you have absolutely no idea.

Thank you very much!

discussion with team thinks this is a recording speed issue. needs fixing for the introlab demo of sudoku to run without producing errors

register_database_notification_request should move from pynn.init to pynn.external_devices.init

The output files seem to be missing the headers

ValueError: operands could not be broadcast together with shapes (27,) (100,)

See
https://github.com/SpiNNakerManchester/sPyNNaker7/tree/master/p7_integration_tests/test_change_neuron_parameters_between_runs

test_run_split or main

In some case the conncetionHolder can throw an IndexError

For example:
import spynnaker7.pyNN as p

p.setup(timestep=1)
pop_1 = p.Population(5, p.IF_curr_exp, {}, label="pop_1")
input = p.Population(5, p.SpikeSourceArray, {'spike_times': [0]},
label="input")
input_proj = p.Projection(input, pop_1,
p.OneToOneConnector(weights=5.0, delays=1),
target="excitatory")
#input_proj= p.Projection(input, pop_1, p.AllToAllConnector(

weights=5.0, delays=1))

repeat_proj = p.Projection(pop_1, pop_1,
p.OneToOneConnector(weights=5.0, delays=1),
target="excitatory")

p.run(20)
weights = input_proj.getWeights(format='array', gather=True)
#weights = input_proj.getWeights(format='list', gather=True)
print weights

Stack Trace:
Traceback (most recent call last):
File "...mini.py", line 19, in
print weights
File "sPyNNaker\spynnaker\pyNN\models\neuron\connection_holder.py", line 205, in str
data = self._get_data_items()
File "sPyNNaker\spynnaker\pyNN\models\neuron\connection_holder.py", line 177, in _get_data_items
connections[item]
IndexError: index 72 is out of bounds for axis 1 with size 5

Note:
Does not happen if I remove the second projection
Does not happen on format="list" (the default)

Not able to replicate in pynn8 so probably not a blocker.