Previous NEST performance benchmarks

Important

NEST version 3.8 benchmarks of the Multi-area-model and HPC benchmark model have been updated due to errors in the analysis! Please see below for corrected versions.

NEST performance is continuously monitored and improved across various network sizes. Here we show benchmarking results for NEST version 3.8 on Jureca-DC [1]. The benchmarking framework and the structure of the graphs is described in [2]. For details on State Propagation (i.e., Simulation Run), see the guides Built-in timers and Simulation behavior

Strong scaling experiment of the Microcircuit model [3]

_images/mc_benchmark_NEST-v3.8.png
  • The model has ~80 000 neurons and ~300 million synapses, minimal delay 0.1 ms

  • 2 MPI processes per node, 64 threads per MPI process

  • Increasing number of computing resources decrease simulation time

  • Data averaged over 3 runs with different seeds, error bars indicate standard deviation

  • The model runs faster than real time [4]

Strong scaling experiment of the Multi-area-model [5]

Dynamical regime: Ground state

_images/mam_ground-state_benchmark_NEST-v3.8.png

Dynamical regime: Metastable state

_images/mam_metastable-state_benchmark_NEST-v3.8.png
  • The model has ~4.1 million neurons and ~24 billion synapses, minimal delay 0.1 ms

  • It can be run in two different dynamical regimes: the ground state and the metastable state [5].

  • 2 MPI processes per node, 64 threads per MPI process

  • Steady decrease of run time with additional compute resources

  • Data averaged over 3 runs with different seeds, error bars indicate standard deviation

Weak scaling experiment of the HPC benchmark model [6]

_images/hpc_benchmark_NEST-v3.8.png
  • The size of network scales proportionally with the computational resources used

  • Largest network size in this diagram: ~5.8 million neurons and ~65 billion synapses, minimal delay 1.5 ms

  • 2 MPI processes per node, 64 threads per MPI process

  • The figure shows that NEST can handle massive networks and simulate them efficiently

  • Data averaged over 3 runs with different seeds, error bars indicate standard deviation

References