# NDSolve memory usage [closed]

I am trying to solve numerically a system of linear ODEs with some quickly varying driving functions. The basic command is: NDSolve[Eqs, Vars, {t, 0, 1}, MaxSteps -> 10^7, MaxStepSize -> 10^(-7), AccuracyGoal -> 10, PrecisionGoal -> 10]; The lists of equations and variables contain 30 elements. My problem is that Mathematica V10.1.0.0 uses inordinate amount of memory, more than 40 GB.

Even if I assume that at each point the interpolation function stores first and second derivatives and it uses double-precision numbers with 8 bytes, I get 10^7*30*8*3=7.2GB.

I tried InterpolationOrder->2 in NDSolve, but that does not reduce the memory used.

• What exactly is your question here? Do you want to find out why it uses so much memory, do you need to reduce memory usage... ? Perhaps sharing the list of equations and variables would be conducive to more specific answers. – MarcoB Feb 3 '16 at 19:20
• The equations would take several pages, but its not relevant, they are just algebraic functions. If I program this in C, my memory usage would just go with the array size of the output as I go along and integrate. So, yes, the question is why does Mathematica use much more memory, if it stores data at intermediate points between each step or something like that and if there is a way to reduce it. Even with 32Gb of RAM, it is starting to swap and slow down. – Mike Feb 3 '16 at 21:01
• Here is a possibility: you are asking for specific accuracy and precision goals, so Mathematica is probably using arbitrary-precision numbers in the calculation. These take much more space in memory than 8 bytes. Consider for instance that machine-precision 3  takes 16 bytes (ByteCount[3]) on my machine, but arbitrary precision 310 occupies a whopping 80 bytes. At that rate with your settings, just storing the function value alone will cost you ca. 20 GB; value + 1st derivative may run into 40 GB or so. Do you see any difference without the accuracy and precision goals? – MarcoB Feb 4 '16 at 2:34
• ByteCount indeed give interesting results. For example: – Mike Feb 5 '16 at 16:25
• For example: ByteCount[{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}]=280 if I type the list explicitly. But ByteCount[Range[10]]=184, ByteCount[Range[10^6]]/10.0^6=8.00014. So it seems asymptotically it uses 8 bytes, but not always. Similarly in NDSolve, sometimes I get InterpolationFunction that uses DeveloperPackedArrayForm and 48 bytes per point. And sometimes I get just a regular-looking array that uses 200 bytes per point. – Mike Feb 5 '16 at 16:37

Maybe this help:

Set up a very large system of equations:

Clear["Global*"]

(Format[#[n_]] := Subscript[#, n]) & /@ x;
X[k_] := x[k];

n = 1000;
vars = Table[X[i][t], {i, n}];
eqns = Table[j = Mod[i, n] + 1; {X[i]'[t] == 1/(X[i][t] + X[j][t])^2,X[i][0] == 1/i}, {i, n}];


Solve for all of the dependent variables, but save only the solution for $x_{1}$:

ONEsol = NDSolve[eqns, X[1], {t, 0, 100},DependentVariables -> vars];


This saves a lot of memory versus saving all the solutions:

ALLsol = NDSolve[eqns, vars, {t, 0, 100}];
{ByteCount[ONEsol], ByteCount[ALLsol]}
(* {16856, 16864248} *)

• You should avoid using Subscript while defining symbols (variables). Subscript[x, 1] is not a symbol, but a compound expression, you expect to do $x_1=2$ but you are actually doing Set[Subscript[x, 1], 2] which is to assign a Downvalue to Subscript and not an Ownvalue to an indexed x as you may intend. Read how to properly define indexed variables here. – rhermans Feb 8 '16 at 20:04
• @rhermans .May the Force be with you :) – Mariusz Iwaniuk Feb 8 '16 at 21:42
• Yes, I figured out that one doesn't have to specify all functions in the list of variables and it will solve for only the functions one needs. That does save about half the memory in my case. Still there seems to be either a bug or a feature, where it generates InterpolatingFunction with "exact" values depending on the NDSolve integration method. It doesn't matter if I include AccuracyGoal and PrecisionGoal or not. And applying N[ ]` to everything doesn't help either. – Mike Feb 9 '16 at 4:47