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@pnbabu pnbabu commented May 7, 2025

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github-actions bot commented May 8, 2025

🐰 Bencher Report

Branch1208/merge
Testbedubuntu-latest

🚨 1 Alert

IterationBenchmarkMeasure
Units
ViewBenchmark Result
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Upper Boundary
(Limit %)
0tests/nest_continuous_benchmarking/test_nest_continuous_benchmarking.py::TestNESTContinuousBenchmarking::test_stdp_nn_synapseLatency
seconds (s)
📈 plot
🚷 threshold
🚨 alert (🔔)
4.03 s
(+18.15%)Baseline: 3.41 s
3.75 s
(107.41%)

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BenchmarkLatencyBenchmark Result
seconds (s)
(Result Δ%)
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seconds (s)
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tests/nest_continuous_benchmarking/test_nest_continuous_benchmarking.py::TestNESTContinuousBenchmarking::test_stdp_nn_synapse📈 view plot
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4.03 s
(+18.15%)Baseline: 3.41 s
3.75 s
(107.41%)

BenchmarkLatencyBenchmark Result
seconds (s)
(Result Δ%)
Upper Boundary
seconds (s)
(Limit %)
tests/nest_continuous_benchmarking/test_nest_continuous_benchmarking.py::TestNESTContinuousBenchmarking::test_stdp_nn_synapse📈 view plot
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3.23 s
(-4.96%)Baseline: 3.40 s
3.74 s
(86.40%)

BenchmarkLatencyBenchmark Result
seconds (s)
(Result Δ%)
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seconds (s)
(Limit %)
tests/nest_continuous_benchmarking/test_nest_continuous_benchmarking.py::TestNESTContinuousBenchmarking::test_stdp_nn_synapse📈 view plot
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3.30 s
(-3.05%)Baseline: 3.40 s
3.74 s
(88.13%)

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clinssen commented Sep 5, 2025

Could you also update running_nest.rst, especially under the heading "Event-based updating of synapses"? Cheers!

The synapse is allowed to contain an ``update`` block. Statements in the ``update`` block are executed whenever the internal state of the synapse is updated from one timepoint to the next; these updates are typically triggered by incoming spikes. The NESTML ``timestep()`` function will return the time that has elapsed since the last event was handled.

Synapses in NEST are not allowed to have any nonlinear time-based internal dynamics (ODEs). This is due to the fact that synapses are, unlike nodes, not updated on a regular time grid. Linear ODEs are allowed, because they admit an analytical solution, which can be updated in a single step from the previous event time to the current event time. However, nonlinear dynamics are not allowed because they would require a numeric solver evaluating the dynamics on a regular time grid.
Synapses can have ODEs with linear and non-linear dynamics. In the case of linear dynamics, the ODEs are solved with the propagators provided by the ODE-toolbox; for non-linear dynamics, the ODEs are solved using a fourth order Runge-Kutta solver with adaptive timestep.
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Can the tolerances be adjusted like in the neuron model? Could you add a reference to GSL or to the GSL solver?

@pnbabu pnbabu requested a review from clinssen October 17, 2025 10:10
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