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Questions about RAM usage, including optimizing memory use, avoiding and fixing leaks and releasing unused memory.

20
votes
[ h0 = h /. FindRoot[h == Fnew[h, b, g], {h, h0}], {b, blist}] ] ], {g, glist}] ]; // AbsoluteTiming // First 10.072 Memory considerations You also see … has certain overhead. In contrast, a packed array represents basically a connected block of physical memory, accompanied by some bytes of meta information (array dimensions and maybe some row …
answered May 19 by Henrik Schumacher
3
votes
Just put N as early as possible to avoid symbolic computations: MaxMemoryUsed[N[Abs[Tanh[Power[N@E, Power[N@Pi, N@E]]]]]] 152
answered Feb 7 '18 by Henrik Schumacher
2
votes
This uses packed arrays throughout and replaces Position with the significantly faster Nearest. (Position[Col, Alternatives @@ col2] needs about Length[Col] Length[col2] operations; Nearest[Col -> Aut …
answered Sep 21 '18 by Henrik Schumacher
4
votes
Maybe you are looking for f[n_Integer?Positive] := Quotient[n, 15] Quotient[n, m] is basically equivalent to Floor[n/m]. The problem of your function is that it needs $O(n)$ memory and $O(n …
answered Mar 24 '18 by Henrik Schumacher
4
votes
(More an extended comment than an answer.) Your spacial resolution is a bit too fine for a common PC. By using the low-level functionalities of "NDSolve`FEM`", I was able to assemple the stiffness …
answered Oct 7 '18 by Henrik Schumacher
3
votes
Since you are using positive integer labels with rather high density in their range you should also try a classical array as lookup table. A further variant that works well when the keys are integers …
answered Sep 16 '18 by Henrik Schumacher
3
votes
For large matrices of numeric values, I suggest to export to the MATLAB MAT-format. This is a binary format for matrices (and tensors) only and thus, it is much faster than exporting arbitrary symbols …
answered Jul 27 '17 by Henrik Schumacher