When a multi-compartment neuron is divided into subtrees such that no subtree has more than two connection points to other subtrees, the subtrees can be on different processors and the entire system remains amenable to direct Gaussian elimination with only a modest increase in complexity. Accuracy is the same as with standard Gaussian elimination on a single processor. It is often feasible to divide a 3-D reconstructed neuron model onto a dozen or so processors and experience almost linear speedup. We have also used the method for purposes of load balance in network simulations when some cells are so large that their individual computation time is much longer than the average processor computation time or when there are many more processors than cells. The method is available in the standard distribution of the NEURON simulation program.

中文翻译：

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单个神经元的完全隐式并行模拟。

当一个多室神经元被分成子树时，没有一个子树与其他子树有两个以上的连接点，这些子树可以在不同的处理器上，整个系统仍然可以直接进行高斯消元，只是稍微增加了复杂性。精度与单个处理器上的标准高斯消除相同。将 3-D 重建神经元模型划分到十几个处理器上并体验几乎线性加速通常是可行的。我们还在网络模拟中使用该方法来实现负载平衡，当某些单元太大以至于它们的单个计算时间比平均处理器计算时间长得多时，或者当处理器比单元多得多时。该方法在 NEURON 模拟程序的标准发行版中可用。