On Parallel Stochastic Simulation of Diffusive Systems

Dematté, Lorenzo; Mazza, Tommaso

doi:10.1007/978-3-540-88562-7_16

Cited by 34 publications

(22 citation statements)

References 26 publications

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“…The conclusion and future work are presented in section 5. [6] points out that a conservative synchronization algorithm for parallel simulation will perform poorly because of the zero-lookahead property of the exponential distribution and the fact that a dependency graph of the reactions is likely to be highly connected and filled with loops. This indicates that an optimistic synchronization algorithm such as Time Warp is preferable.…”

Section: Introductionmentioning

confidence: 98%

NTW-Mt

Lin

Tropper

Patoary

et al. 2015

Proceedings of the 3rd ACM SIGSIM Conference on Principles of Advanced Discrete Simulation

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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. The simulator was developed as part of the NEURON project and is intended to be included in NEURON. It relies upon a stochastic discrete event model developed for chemical reactions. NTW-MT is optimistic and thread-based, in which communication latency among threads within the same process is minimized by pointers. We investigate the performance of NTW-MT on a reaction-diffusion model for the transmission of calcium waves in a neuron. Calcium plays a fundamental role in the second messenger system of a neuron. However, the mechanism by which calcium waves are transmitted is not entirely understood. Stochastic models are more realistic than deterministic models for small populations of ions such as those found in apical dendrites. To be more precise, we simulate a stochastic discrete event model for calcium wave propagation on an unbranched apical dendrite of a hippocampal pyramidal neuron. We examine the performance of NTW-MT on this calcium wave model and compare it to the performance of (1) a process based op- * This author is affiliated with State timistic simulator and (2) a threaded simulator which uses a single priority (SQ) queue for each thread. Our multithreaded simulator is shown to achieve superior performance to these simulators.

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Section: Introductionmentioning

confidence: 98%

NTW-Mt

Lin

Tropper

Patoary

et al. 2015

Proceedings of the 3rd ACM SIGSIM Conference on Principles of Advanced Discrete Simulation

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“…In contrast, LPs can keep processing events and employ roll-back to recover incorrectly-processed events in optimistic protocols. [13] points out that a conservative synchronization algorithm for this kind of simulation will perform poorly because of the zero-lookahead property of the exponential distribution and the fact that a dependency graph of the reactions is likely to be highly connected and filled with loops. This indicates that an optimistic synchronization algorithm such as Time Warp [14] is preferable.…”

Section: Introductionmentioning

confidence: 98%

Parallel Discrete Event Simulation of Stochastic Reaction and Diffusion Using Reverse Computation

Lin

Yao

2015

2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity)

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Parallel discrete event simulation consumes massive memory, involves frequent allocation and deallocation, and generates huge amount of data, which makes the memory usage an important issue for performance. In this paper, we present our reverse computation approach in our multi-threaded parallel discrete event simulator used for large scale stochastic reactiondiffusion simulation. We compute the reverse control code to record what operation an event did on the state of the host Logical Process during forward processing, and undo the operation according to the corresponding code during recovering that event.As the results on two versions of calcium wave model show, the reverse computation version achieved better performance than the state-saving version-it saved about 33% and 36% execution time for the two models respectively when two processing threads were used.

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“…In computational biology the biochemical systems (e.g. reaction-diffusion systems), can be modeled as discrete event systems [2] and can be simulated in parallel.…”

Section: Introductionmentioning

confidence: 99%

Parallel Stochastic Discrete Event Simulation of Calcium Dynamics in Neuron

Patoary

Tropper

McDougal

et al. 2019

IEEE/ACM Trans. Comput. Biol. and Bioinf.

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the correctness and performance of NTW by comparing it to a sequential deterministic simulation in NEURON. The derivation of a discrete event calcium wave model using the stochastic IP 3 R structure is one of my main scientific contributions of this thesis. This newly derived stochastic discrete event calcium wave model is described in chapter-5. In high performance issue, a dynamic load balancing algorithm and a dynamic window control algorithm for NTW was also developed for the stochastic calcium wave model. We use Q-learning to determine the basic control parameters of the algorithm. Prof. Tropper motivated me to employ Q-learning to optimize the performance of NTW in calcium wave simulation. Developing such an intelligent dynamic load balancing algorithm with dynamic window control is another research contribution of this thesis. All algorithms are described in chapter 6. vi ABSTRACTThe intra-cellular calcium signaling pathways of a neuron depends on both biochemical reactions and diffusions. Some quasi-isolated compartments (e.g. spines) are so small and the calcium concentrations are so low that one molecule diffusing into the compartment can make a nontrivial difference in calcium concentration. Such events can affect dynamics discretely in such a way that they cannot be evaluated by a deterministic simulation. Stochastic models of such a system provide a more detailed understanding of these systems than existing deterministic models because they capture their behavior at a molecular level. My research focuses on the development of a high performance parallel discrete event simulation environment, NTW , which is intended for use in the parallel simulation of stochastic reaction-diffusion systems such as intra-cellular calcium signaling. We make use of two models, a calcium buffer model and a calcium wave model. The calcium buffer model is employed in order to verify the correctness and performance of NTW by comparing it to a sequential deterministic simulation in NEURON. NEURON is a framework for simulating neurons which is used by neuroscientists world-wide. Our work is part of the NEURON project and has the long term goal of developing a multiscale simulation for large scale neuronal networks. We derived a discrete event calcium wave model from a deterministic model using the stochastic inositol 1,4,5-trisphosphate receptors, IP 3 R, structure. A dynamic load balancing algorithm and a dynamic window control algorithm for NTW was also developed for the stochastic calcium wave model.We make use of Q-learning to determine the basic control parameters of the algorithm.

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On Parallel Stochastic Simulation of Diffusive Systems

Cited by 34 publications

References 26 publications

NTW-Mt

NTW-Mt

Parallel Discrete Event Simulation of Stochastic Reaction and Diffusion Using Reverse Computation

Parallel Stochastic Discrete Event Simulation of Calcium Dynamics in Neuron

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