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The NEST Dry-Run Mode: Efficient Dynamic Analysis of Neuronal Network Simulation Code
2017
Frontiers in Neuroinformatics
NEST is a simulator for spiking neuronal networks that commits to a general purpose approach: It allows for high flexibility in the design of network models, and its applications range from small-scale simulations on laptops to brain-scale simulations on supercomputers. Hence, developers need to test their code for various use cases and ensure that changes to code do not impair scalability. However, running a full set of benchmarks on a supercomputer takes up precious compute-time resources and
doi:10.3389/fninf.2017.00040
pmid:28701946
pmcid:PMC5487483
fatcat:a7z7cyqhtrbunaoggybaimtqwm