Fully implicit parallel simulation of single neurons
Fully implicit parallel simulation of single neurons
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DOI：
10.1007/s10827-008-0087-5
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发表时间：
2008-12-01
影响因子：
1.2
通讯作者：
Schuermann, Felix
中科院分区：
文献类型：
--
作者：
Hines, Michael L.;Markram, Henry;Schuermann, Felix
当多隔室神经元被划分成子树，使得没有子树具有到其他子树的两个以上的连接点时，子树可以在不同的处理器上，并且整个系统仍然适合于直接高斯消除，而复杂度仅适度增加。精度与单个处理器上的标准高斯消去法相同。通常可以将一个3D重建的神经元模型划分到十几个处理器上，并经历几乎线性的加速。我们还使用的方法在网络模拟中的负载平衡的目的时，一些细胞是如此之大，他们的个人计算时间比平均处理器的计算时间要长得多，或者当有更多的处理器比细胞。该方法可在标准分布的NEURON仿真程序中实现。
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.