Supplementary Material for: On the Accuracy and Computational Cost of Spiking Neuron Implementation

This data contains the Supplementary material for the paper "On the Accuracy and Computational Cost of Spiking Neuron Implementation." This is divided into five folders: 1) Source code, 2) Raw data, 3) Calculations, 4) Tables, and 5) Figures. The Source code folder has the script files wri...

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Bibliographische Detailangaben
1. Verfasser: Valadez-Godínez, Sergio
Format: Dataset
Sprache:eng
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Zusammenfassung:This data contains the Supplementary material for the paper "On the Accuracy and Computational Cost of Spiking Neuron Implementation." This is divided into five folders: 1) Source code, 2) Raw data, 3) Calculations, 4) Tables, and 5) Figures. The Source code folder has the script files written in Python 3.7.3. There are two sub-folders inside this folder separating the scripts into constant and random input current tests, respectively. Each sub-folder has a separate Python script that performs a benchmark test for each Spiking Neuron (SN) model. The Raw data folder collects the data generated by executing the scripts in the Source code folder and by following the instructions in the Testing procedure section of the paper. This stores the raw data for several SNs, firing frequencies, and input currents. This folder has a sub-folder with several files recording the random input currents used in the benchmark tests. The Raw data folder also has two sub-folders with the benchmark test results, each for a specific stimulation current type. The Benchmark test sub-folders give the CPU execution time, the SCF (Spike Coincidence Factor), the VCF (Voltage Coincidence Factor), the last spike displacement, and the firing frequency for each Numerical Method (NM) and time step. Other four sub-folders are containing the spike-timing and voltage time course data. These data are separated into constant and random input currents and NM and time step. The Calculations folder gives two files in .xlsx format with several estimates used in the paper. These files collect the CPU time, SCF, VCF, last spike displacement, and firing frequency from Raw data folder and compute the CCF (Computational Cost Factor) and GPF (Global Performance Factor) for several SNs and firing frequencies. Also, these files calculate the average and increment/decrement percent in FLOPS, CPU time, CCF, SCF, VCF, last spike displacement, and GPF among several SNs and NMs. Furthermore, these files examine the balanced, lower limit, upper limit, Skocik-Long, and Izhikevich configurations mentioned in the paper. Fourth and fifth folders contain the supplementary tables and figures, respectively, referenced in the article.
DOI:10.17632/b3y8pktb6h