Computational speed when the array dimension is large

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Shujie Zhao
Shujie Zhao on 15 Nov 2021
Commented: James Tursa on 15 Nov 2021
The 4th-order Runge-Kutta numerical method is applied to drive the time-domain responses of a second order differential equation, where the unknown motion is a function of time. I find that the speed of the operation drops dramatically when my simulation time becomes longer. How can I improve the speed of the program? I compared calculation speed between 200s and 7200s simulation time and the drop in running speed was noticeable. The length of all variables are pre-defined before the loop.The simulated time step is 0.01s, and the computer processor is "Intel Xeon W-2295, 18 Cores, 36 Threads, 3.0GHz, 4.8GHz Turbo" and the memory is 64GB (4*16GB) DDR4-2933 REG ECC.
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James Tursa
James Tursa on 15 Nov 2021
Please post the differential equation you are solving and the code you are using. It is very hard to suggest improvements without seeing these details.

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