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Analytic Performance Modeling and Analysis of Detailed Neuron Simulations [article]

Francesco Cremonesi, Georg Hager, Gerhard Wellein, Felix Schürmann
2019 arXiv   pre-print
We present a detailed study of the shared-memory performance of morphologically detailed neuron simulations based on the Execution-Cache-Memory (ECM) performance model.  ...  optimizations and eventually drive co-design efforts, but to our knowledge a model-based performance analysis of neuron simulations has not yet been conducted.  ...  We are also indebted to the Blue Brain HPC team for helpful support and discussion regarding CoreNEURON.  ... 
arXiv:1901.05344v1 fatcat:b4tfyvyqqvh3pn3qj7xacvjclm

Supplemental Material, Rebuttal_BBP-IJHPCA_2019 - Analytic performance modeling and analysis of detailed neuron simulations

Francesco Cremonesi, Georg Hager, Gerhard Wellein, Felix Schürmann
2020 Figshare  
Supplemental Material, Rebuttal_BBP-IJHPCA_2019 for Analytic performance modeling and analysis of detailed neuron simulations by Francesco Cremonesi, Georg Hager, Gerhard Wellein and Felix Schürmann in  ...  The International Journal of High Performance Computing Applications  ...  The list entry was removed • Like in every experimental performance analysis, the results may be input dependent.  ... 
doi:10.25384/sage.12083595.v1 fatcat:evnam3e5srgelhs3qcdx7qpy4e

An Optimizing Multi-platform Source-to-source Compiler Framework for the NEURON MODeling Language [chapter]

Pramod Kumbhar, Omar Awile, Liam Keegan, Jorge Blanco Alonso, James King, Michael Hines, Felix Schürmann
2020 Lecture Notes in Computer Science  
Here, we describe a new code generation framework (NMODL) for an existing DSL in the NEURON framework, a widely used software for massively parallel simulation of biophysically detailed brain tissue models  ...  When comparing NMODL-generated kernels with NEURON we observe a speedup of up to 20×, resulting in overall speedups of two different production simulations by ∼7×.  ...  The research was also funded by NIH grant number R01NS11613 to the Department of Neuroscience, Yale University, and the European Union's Horizon 2020 Framework Programme for Research and Innovation under  ... 
doi:10.1007/978-3-030-50371-0_4 fatcat:srbmqwowvrdmzkurbuavxri7lm

An optimizing multi-platform source-to-source compiler framework for the NEURON MODeling Language [article]

Pramod Kumbhar, Omar Awile, Liam Keegan, Jorge Blanco Alonso, James King, Michael Hines, Felix Schürmann
2019 arXiv   pre-print
Here, we describe a new code generation framework (NMODL) for an existing DSL in the NEURON framework, a widely used software for massively parallel simulation of biophysically detailed brain tissue models  ...  When comparing NMODL-generated kernels with NEURON we observe a speedup of up to 20x, resulting into overall speedups of two different production simulations by ∼10x.  ...  We would like to thank Antonio Bellotta, Francesco Cremonesi, Ioannis Magkanaris, Matthias Wolf, Samuel Melchior and Tristan Carel for fruitful discussions and their contributions to the NMODL development  ... 
arXiv:1905.02241v1 fatcat:3wcl7sasiffehc65rp3cabbuym

Admittance Method for Estimating Local Field Potentials Generated in a Multi-Scale Neuron Model of the Hippocampus

Clayton S. Bingham, Javad Paknahad, Christopher B. C. Girard, Kyle Loizos, Jean-Marie C. Bouteiller, Dong Song, Gianluca Lazzi, Theodore W. Berger
2020 Frontiers in Computational Neuroscience  
discretized and numerically solved volume conduction models and biologically detailed neural circuit models constructed in NEURON.  ...  Establishing this method is a critical step toward closed-loop integration of volume conductor and NEURON models that could lead to substantial improvement of the predictive power of multi-scale stimulation  ...  ACKNOWLEDGMENTS The authors thank Sydney Nguyen and Daniel Nemeth for testing the models used in this study and suggesting various improvements to the codebase in preparation for software distribution.  ... 
doi:10.3389/fncom.2020.00072 pmid:32848687 pmcid:PMC7417331 fatcat:cnb72635wncezfkdzgo5cylr7i

On the use of analytic expressions for the voltage distribution to analyze intracellular recordings [article]

Michelle Rudolph, Alain Destexhe
2006 arXiv   pre-print
Different analytic expressions for the membrane potential distribution of membranes subject to synaptic noise have been proposed, and can be very helpful to analyze experimental data.  ...  However, all of these expressions are either approximations or limit cases, and it is not clear how they compare, and which expression should be used in a given situation.  ...  Acknowledgments Research supported by CNRS and the Human Frontier Science Program. Supplementary information can be found at http://cns-iaf.cnrs-gif.fr  ... 
arXiv:q-bio/0602010v1 fatcat:s4sjpcjs4bfkbif43atfwkdlra

Telling neuronal apples from oranges: analytical performance modeling of neural tissue simulations [article]

Francesco Cremonesi, Felix Schürmann
2019 arXiv   pre-print
bottlenecks as the number of neurons to be simulated grows.  ...  For the first time, we present a systematic exploration based on analytic performance modeling.  ...  ECM model and the interpretation of performance predictions.  ... 
arXiv:1906.02757v1 fatcat:rky6l5t6ovfldm6qluyysn5rhy

STDP encodes oscillation frequencies in the connections of recurrent networks of spiking neurons

Robert R Kerr, Anthony N Burkitt, Doreen A Thomas, David B Grayden
2012 BMC Neuroscience  
BMC Neuroscience 2012, 13(Suppl 1):P130 delays receiving oscillatory inputs were investigated analytically with the Poisson neuron model and verified through simulations with leaky integrate-and-fire (  ...  The analysis and simulations found that connections were selectively potentiated and depressed based on their axonal delay in such a way that the delays of the strong connections in the network "resonated  ...  These are realistic for neurons/synapses found in the auditory brainstem. delays receiving oscillatory inputs were investigated analytically with the Poisson neuron model and verified through simulations  ... 
doi:10.1186/1471-2202-13-s1-p130 pmcid:PMC3403623 fatcat:7rauahtuhjfxjdprk3codxvfia

Granger causality analysis of fMRI BOLD signals is invariant to hemodynamic convolution but not downsampling

Anil K. Seth, Paul Chorley, Lionel C. Barnett
2013 NeuroImage  
Our methods, which include detailed spiking neuronal models coupled to biophysically realistic hemodynamic observation models, provide an important 'analysis-agnostic' platform for evaluating functional  ...  Granger causality is a method for identifying directed functional connectivity based on time series analysis of precedence and predictability.  ...  Mortimer and Theresa Sackler Foundation (AKS and LB) via the Sackler Centre for Consciousness Science. We thank Adam Barrett for helpful discussions, and four reviewers for their insightful comments.  ... 
doi:10.1016/j.neuroimage.2012.09.049 pmid:23036449 fatcat:vlaklpkiuvglzamis4r2i5ygzm

NNVA: Neural Network Assisted Visual Analysis of Yeast Cell Polarization Simulation [article]

Subhashis Hazarika, Haoyu Li, Ko-Chih Wang, Han-Wei Shen and Ching-Shan Chou
2019 arXiv   pre-print
We utilize the trained network to perform interactive parameter sensitivity analysis of the original simulation at multiple levels-of-detail as well as recommend optimal parameter configurations using  ...  We also facilitate detail analysis of the trained network to extract useful insights about the simulation model, learned by the network, during the training process.  ...  ACKNOWLEDGMENTS This work was supported in part by US Department of Energy Los Alamos National Laboratory contract 47145 and UT-Battelle LLC contract 4000159447 program manager Laura Biven.  ... 
arXiv:1904.09044v2 fatcat:qme7g237ifdehoke3c7e72fl7y

A Network Simulator for the Estimation of Bandwidth Load and Latency Created by Heterogeneous Spiking Neural Networks on Neuromorphic Computing Communication Networks

Robert Kleijnen, Markus Robens, Michael Schiek, Stefan van Waasen
2022 Journal of Low Power Electronics and Applications  
This simulator allows simulating the impacts of heterogeneous neural networks and evaluating neuron mapping algorithms, which is a unique feature among state-of-the-art network models and simulators.  ...  Novel many-core simulation platforms, e.g., SpiNNaker, BrainScaleS and Neurogrid, allow one to study neuron behavior in the brain at an accelerated rate, with a high level of detail.  ...  The multi-area model simulations were performed for N pN = 100, 250, 500 and N pN = 1000.  ... 
doi:10.3390/jlpea12020023 fatcat:suxzq52e7rdl3glec33hhgthe4

Mathematical Modeling and Analysis of Spatial Neuron Dynamics: Dendritic Integration and Beyond

Songting Li, David W. McLaughlin, Douglas Zhou
2021 Communications on Pure and Applied Mathematics  
of neuronal simulation incorporating certain important dendritic functions.  ...  Based on the passive cable theory, a PDE-based cable neuron model with spatially branched dendritic structure is introduced to describe the neuronal subthreshold membrane potential dynamics, and the analytical  ...  Here the perturbation analysis is performed on the cable neuron model with branched dendritic structure, and synaptic inputs can be elicited on any dendritic site of the neuron.  ... 
doi:10.1002/cpa.22020 fatcat:jpefe2pb4nc4zjtkc6kwf2i5g4

Accurate angular integration with only a handful of neurons [article]

Marcella Noorman, Brad K Hulse, Vivek Jayaraman, Sandro Romani, Ann M Hermundstad
2022 bioRxiv   pre-print
We then analytically determined how performance degrades as the connectivity deviates from this optimally-tuned setting, and we find a trade-off between network size and the tuning precision needed to  ...  Motivated by the peak performance of the fly head direction system in darkness, we mathematically derived conditions under which small networks, even with as few as 4 neurons, achieve the performance of  ...  VJ performed data analysis, with primary input from BKH, and additional input from MN, SR, and AMH. MN performed the bulk of the analytics, with contributions from SR and AMH.  ... 
doi:10.1101/2022.05.23.493052 fatcat:sbc5h4c7oreyflim2yebqzqevi

A recurrent model of transformation invariance by association

Martin C.M Elliffe, Edmund T Rolls, Néstor Parga, Alfonso Renart
2000 Neural Networks  
The simulation implements the analytic model of Parga and Rolls [(1998) . Transform-invariant recognition by association in a recurrent network.  ...  The simulations also extended the analysis by showing that the system could work well with sparse patterns; and showing how pattern sparseness interacts with the number of views of each object (as a result  ...  The form of these curves matches the simulation performance curves in great detail, with the number and location (in a) of performance peaks and troughs all but identical.  ... 
doi:10.1016/s0893-6080(99)00096-9 pmid:10935762 fatcat:pxgh54c5x5g45gca7b3qds7eri

A mean-field toolbox for spiking neuronal network model analysis [article]

Moritz Layer, Johanna Senk, Simon Essink, Alexander van Meegen, Hannah Bos, Moritz Helias
2021 bioRxiv   pre-print
Mean-field theory of spiking neuronal networks has led to numerous advances in our analytical and intuitive understanding of the dynamics of neuronal network models during the past decades.  ...  and linear response approximation, without running simulations on high performance systems.  ...  to analytical linear stability analysis, as described in detail in Senk et al. (2020, A.  ... 
doi:10.1101/2021.12.14.472584 fatcat:q5tecm24mzg67b6avnriwbygdq
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