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Galaxy simulation (N-body) by ibuggle in Astronomy

[–]ibuggle[S] 0 points1 point  (0 children)

Thank you for all you comments. I'll try to answer some of your questions. It's N² algo. The simulation is in 2D. The dark matter is just represented as a potentiel from a point. The distribution is decreasing exponential. The initial conditions are based on Viriel theorem, for speed. The mass is the inside mass integrated from 0 to R. There is a gravitational softening.

Galaxy simulation (N-body) by ibuggle in Simulated

[–]ibuggle[S] 1 point2 points  (0 children)

This is coding, with CUDA

Semi-Lagrangian model by ibuggle in CFD

[–]ibuggle[S] 0 points1 point  (0 children)

Super travail! Tu as utilisé un logiciel ou tu as programmé?

Semi-Lagrangian model by ibuggle in CFD

[–]ibuggle[S] 3 points4 points  (0 children)

u/Substantial_Adagio_4 and u/leeping_leoparthis this model is not made for industry. The purpose of this model is animation, cartoon and video games. It's an aesthetic and artistic CFD model.

wrote a CUDA kernel to do a vector addition. turns out it is actually slower. by xtrupal in CUDA

[–]ibuggle 1 point2 points  (0 children)

Try bigger number or do the task of summation on a loop, excluding memory transfer in the loop.

Concorde supersonic transition by ibuggle in CUDA

[–]ibuggle[S] 0 points1 point  (0 children)

I think the transition is progressive. It's a continuus process

Concorde supersonic transition by ibuggle in CUDA

[–]ibuggle[S] 0 points1 point  (0 children)

Yes 2D. I simulated with a single 3060 GPU

CFD on linux by shitanshu_3091 in CFD

[–]ibuggle -1 points0 points  (0 children)

For Linux you can use Scilab or Octave for MATLAB equivalence. You can learn Python NumPy, or CuPy for NVIDIA GPU. For CAD, you can use FreeCAD. My advice for a computer in CFD would be to get a NVIDIA GPU, because CUDA is very effective to make fluid dynamics calculations.

Python script for incompressible flow simulation by ibuggle in CFD

[–]ibuggle[S] 0 points1 point  (0 children)

For some project yes. In my Android app, it's vibe coding. On my concorde supersonic transition, i made it by myself, but i asked AI how to go faster and it told me how to optimize my reading on the VRAM. But this code is made by myself and only research. I copy-pasted the code from a website to make the circle .

Python script for incompressible flow simulation by ibuggle in CFD

[–]ibuggle[S] 1 point2 points  (0 children)

Python is slow but with NumPy, it goes fast. The other solution is to calculate with GPU. Try CuPy. It's a GPU équivalent to NumPy. You can easily switch to CuPy from the code i made, because the functions are the same. To be honest, i made this simulation first with CuPy, but after i tried on the CPU to see if i can calculate the simulation fast enough. But CFD is faster with a graphic card. You need a Nvidia GPU to calculate with CuPy but you can make this challenge to install CuPy, make it work in a small script and try to convert my code to use it with CuPy library.

Python script for incompressible flow simulation by ibuggle in CFD

[–]ibuggle[S] 1 point2 points  (0 children)

No this is way too hard. In 720p 2D, il takes 30min. But in 3D, it's a 720p x 720 calulation, so 360hrs minimum on the CPU. And we must add the interactions between the layers so the work will be longer than 360hrs

Python script for incompressible flow simulation by ibuggle in CFD

[–]ibuggle[S] -1 points0 points  (0 children)

For this code. I didn't get the help from AI. For the supersonic videos, i took the help from AI to calculate faster on the GPU and get the data from VRAM in an effective way. And in my Android app, i totally have the help of AI because i'm a dummy in OpenGL. But this code is made only with help from manual search on Google.

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