Multithreaded Stochastic PDES for Reactions and Diffusions in Neurons

Abstract

Cells exhibit stochastic behavior when the number of molecules is small. Hence a stochastic reaction-diffusion simulator capable of working at scale can provide a more accurate view of molecular dynamics within the cell. This paper describes a parallel discrete event simulator, Neuron Time Warp-Multi Thread (NTW-MT), developed for the simulation of reaction diffusion models of neurons. To the best of our knowledge, this is the first parallel discrete event simulator oriented towards stochastic simulation of chemical reactions in a neuron. The simulator was developed as part of the NEURON project. NTW-MT is optimistic and thread-based, which attempts to capitalize on multi-core architectures used in high performance machines. It makes use of a multi-level queue for the pending event set and a single roll-back message in place of individual anti-messages to disperse contention and decrease the overhead of processing rollbacks. Global Virtual Time is computed asynchronously both within and among processes to get rid of the overhead for synchronizing threads. Memory usage is managed in order to avoid locking and unlocking when allocating and de-allocating memory and to maximize cache locality. We verified our simulator on a calcium buffer model. We examined its performance on a calcium wave model, comparing it to the performance of a process based optimistic simulator and a threaded simulator which uses a single priority queue for each thread. Our multi-threaded simulator is shown to achieve superior performance to these simulators. Finally, we demonstrated the scalability of our simulator on a larger CICR model and a more detailed CICR model.

Efficient simulation of 3D reaction-diffusion in models of neurons and networks

“…The second alternative approach is to use multisimulation; that is, to combine a solver specializing in ion channels and the cable equation like NEURON or MOOSE (Dudani et al, 2009) with an external solver specializing in reactiondiffusion simulation. We and our colleagues have used this approach for stochastic 3D model simulation with NEURON Time Warp (Lin et al, 2017). KappaNEURON likewise combines NEURON with the rule-based reaction-diffusion simulator SpatialKappa (Sterratt et al, 2014).…”

Efficient Simulation of 3D Reaction-Diffusion in Models of Neurons and Networks

“…The second alternative approach is to use multisimulation; that is, to combine a solver specializing in ion channels and the cable equation like NEURON or MOOSE ( RRID:SCR_008031 ; Dudani et al, 2009 ) with an external solver specializing in reaction-diffusion simulation. We and our colleagues have used this approach for stochastic 3D model simulation with NEURON Time Warp (Lin et al, 2017 ). KappaNEURON likewise combines NEURON with the rule-based reaction-diffusion simulator SpatialKappa (Sterratt et al, 2014 ).…”

Using NEURON for Reaction-Diffusion Modeling of Extracellular Dynamics

“…The term mosaic modeling may be used to describe these complex multiscale, multiphysics, multialgorithmic, multidimensional simulations—the mosaic involves pieces of a cell or of a brain simulated with different dimensionality, different algorithms, and different discretizations. An example at the cellular level are spines, which are best handled stochastically and in three dimensions, while the rest of the cell is handled deterministically and as a one dimensional branched tree structure (Lin et al, 2017a , b ). Similarly, in the ECS, small spaces such as synapses require a microscopic approach that is not practical for bulk tissue modeling.…”