The name is absent

Ill

Table 4.1: Top section: Performance of reduced strong-weak model of the MIG fiber as
compared with the full model. Here k_w = 10, N = 1001, and xτ is located 500 pm from
the distal end. Middle section: Same as the top section, but now xτ is located 400 pm from
the distal end. Bottom sect ion performance of the POD+DEIM model (here k_v = k∣) on
the same fiber with the same inputs.

Reduced strong-weak model:			xτ located 500 pm from distal end
k_s	Speed-up	% Matched	% Mismatched	Γ
10	3.2×	98.9	15.7	0.905
20	2.9×	98.1	2.3	0.978
25	2.7×	98.5	________3.4______	0.974
Reduced strong-weak model:			xτ located 400 pm from distal end
	Speed-up	% Matched	% Mismatched	Γ
10	3.3×	98.9	22.4	0.863
20	3.0×	97.7	3.4	0.970
25	2.7×	98.5	2.3	0.980

POD+DEIM model

ky	Speed-up	% Matched	% Mismatched	Γ
10	5.5×	75.4	12.5	0.807
20	5.0×	95.8	3.1	0.962
25	4.6×	99.2	0.8	0.992

4.2 Generalizing the Strong-Weak Model to Arbitrary Mor-

phologies

The RSW model can be extended to handle arbitrary branched neurons, with two
main changes that must be considered. First, in partitioning the cell into strong and
weak components, there is a possibility that the branches of the individual compo-
nents will not be ordered to take advantage of the improvements of (Hines, 1984) that
permit efficient Gaussian Elimination. Hence we must reorder the branches locally
and reindex the compartments locally in order to achieve this result. Second, the

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