ArticleFrontiers in neuroinformatics2017
Parallel STEPS: Large Scale Stochastic Spatial Reaction-Diffusion Simulation with High Performance Computers.
Article in Frontiers in neuroinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- A 3D-1D-0D multiscale model of the neuro-glial-vascular unit for synaptic and vascular dynamics in the dorsal vagal complex.Journal of mathematical biology · 2025Article
- Parallelization of Particle-Based Reaction-Diffusion Simulations Using MPI.Journal of computational chemistry · 2025Article
- Dynamic regulation of vesicle pools in a detailed spatial model of the complete synaptic vesicle cycle.Science advances · 2025Article
- Vesicle and reaction-diffusion hybrid modeling with STEPS.Communications biology · 2024Article
- Ultraliser: a framework for creating multiscale, high-fidelity and geometrically realistic 3D models for in silico neuroscience.Briefings in bioinformatics · 2023Article
- STEPS 4.0: Fast and memory-efficient molecular simulations of neurons at the nanoscale.Frontiers in neuroinformatics · 2022Article
- The Role ofFrontiers in digital health · 2022Review
- Computational models of neurotransmission at cerebellar synapses unveil the impact on network computation.Frontiers in computational neuroscience · 2022Review
- A first-passage approach to diffusion-influenced reversible binding and its insights into nanoscale signaling at the presynapse.Scientific reports · 2021Article
- Quantifying the roles of space and stochasticity in computer simulations for cell biology and cellular biochemistry.Molecular biology of the cell · 2021Article
- 3D mesh processing using GAMer 2 to enable reaction-diffusion simulations in realistic cellular geometries.PLoS computational biology · 2020Article
- pSpatiocyte: a high-performance simulator for intracellular reaction-diffusion systems.BMC bioinformatics · 2020Article
- Applications and Challenges of Machine Learning to Enable Realistic Cellular Simulations.Frontiers in physics · 2020Article
- Simulation of calcium signaling in fine astrocytic processes: Effect of spatial properties on spontaneous activity.PLoS computational biology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Stochastic, spatial reaction-diffusion simulations have been widely used in systems biology and computational neuroscience. However, the increasing scale and complexity of models and morphologies have exceeded the capacity of any serial implementation. This led to the development of parallel solutions that benefit from the boost in performance of modern supercomputers. In this paper, we describe an MPI-based, parallel operator-splitting implementation for stochastic spatial reaction-diffusion simulations with irregular tetrahedral meshes. The performance of our implementation is first examined and analyzed with simulations of a simple model. We then demonstrate its application to real-world research by simulating the reaction-diffusion components of a published calcium burst model in both Purkinje neuron sub-branch and full dendrite morphologies. Simulation results indicate that our implementation is capable of achieving super-linear speedup for balanced loading simulations with reasonable molecule density and mesh quality. In the best scenario, a parallel simulation with 2,000 processes runs more than 3,600 times faster than its serial SSA counterpart, and achieves more than 20-fold speedup relative to parallel simulation with 100 processes. In a more realistic scenario with dynamic calcium influx and data recording, the parallel simulation with 1,000 processes and no load balancing is still 500 times faster than the conventional serial SSA simulation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.