Cell splitting in neural networks extends strong scaling (Hines et al. 2008)

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Accession:97917
Neuron tree topology equations can be split into two subtrees and solved on different processors with no change in accuracy, stability, or computational effort; communication costs involve only sending and receiving two double precision values by each subtree at each time step. Application of the cell splitting method to two published network models exhibits good runtime scaling on twice as many processors as could be effectively used with whole-cell balancing.
Reference:
1 . Hines ML, Eichner H, Schürmann F (2008) Neuron splitting in compute-bound parallel network simulations enables runtime scaling with twice as many processors. J Comput Neurosci 25:203-10 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Generic;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Methods;
Implementer(s): Hines, Michael [Michael.Hines at Yale.edu];
// division information format is a leaf to root ordered list of
// sid sectionname hostid
// where each triple refers to the subtree for which the triple defines
// the root of the subtree.
// Note that root of the whole cell defines a subtree which is what is
// left over when all other subtrees have been disconnected. Some point
// on this subtree (typically for convenience, soma(0)) should be the
// last item in the list and may have a sid of -1. In fact the only information
// used in the last item is the host field which defines where it will
// continue to exists.
// Note that consistency requires that if two pairs have the same parent
// then they must also have the same sid.
// Also required is that there cannot be more than two distinct connection
// points into the root subtree from other subtrees. Furthermore, there
// can only be at  most one connection point into a non-root subtree from
// other (child) subtrees.

// args are sid Vector, SectionRefList, host vector
// Note that any subtree with a host != pc.id is deleted.

// This algorithm allows multiple subtrees from the same cell on
// one cpu. In fact all the subtrees can be on one cpu.

// Note: occasionally the root  parent piece (containing the soma)
// is an orphan at its sid == 0 (root)
// in the sense that
// no other piece connects to that location. This is naturally handled
// in that we do not call multisplit at that point and so there is
// no wasteful backbone.


proc multisplit_divide() {local i, x \
 localobj sids, subroots, subroot, hosts, sr, sl1, sl2, pc, parents, px
	pc = ParallelContext[0]
	sids = $o1
	subroots = $o2
	hosts = $o3
	// sl1 is the whole tree
	sl1 = new SectionList()
	$o2.object(0).sec { sl1.wholetree }
	// create a parallel list of true_parent SectionRef and parent
	// connection points. We use that to help construct the parents
	// parent to child multisplit connection near the end.
	parents = new List()
	px = new Vector()
	for i=0, subroots.count - 2 { // do not use the root subtree
		subroot = subroots.object(i)
		if (subroot.has_parent) { // if not then root(0)
			subroot.parent parents.append(new SectionRef())
			subroot.sec px.append(parent_connection())
		}else{
			subroot.root parents.append(new SectionRef())
			px.append(0)
		}
	}	
	// now disconnect leaving only subtrees
	for i=0, subroots.count - 2 {
		subroots.object(i).sec disconnect()
	}
	// delete any subtree not on this cpu.
	for i=0, subroots.count - 1 {
		if (hosts.x[i] != pc.id) {
			sl1 = new SectionList()
			subroots.object(i).sec sl1.wholetree()
			forsec sl1 delete_section()
		}
	}
	// now we can do the multisplit for each subroot
	for i=0, subroots.count - 2 {
		if (subroots.object(i).exists()) subroots.object(i).sec {
//printf("%d %s pc.multisplit(%g, %d, 2)\n", pc.id, secname(), 0, sids.x[i])
			pc.multisplit(0, sids.x[i], 2)
			// and it will be helpful to initialize v marks
			sl1 = new SectionList()
			sl1.wholetree()
			forsec sl1 v = -1
		}
	}
	// mark all the subtree parents
	for i=0, subroots.count - 2 {
		if (parents.object(i).exists()) parents.object(i).sec {
			v(px.x[i]) = -1
		}
	}
	// and we can do the multisplit for the parents
	// but we should only do any given parent location once
	// (that is why we find the v mark useful)
	for i=0, subroots.count - 2 {
		if (parents.object(i).exists()) parents.object(i).sec {
			if (v(px.x[i]) == -1) { // multisplit needs to be done
//printf("%d %s pc.multisplit(%g, %d, 2)\n", pc.id, secname(), px.x[i], sids.x[i])
				pc.multisplit(px.x[i], sids.x[i], 2)
				v(px.x[i]) = sids.x[i]
			}else if (v(px.x[i]) != sids.x[i]) { // sanity check
printf("i=%d px.x[i]=%d v=%g sids.x[i]=%g\n", i, px.x[i], v(px.x[i]), sids.x[i])
				execerror("Subtrees at same parent with different sid", "")
			}
		}
	}
}