alt Hacker News> The spice core that ngspice is built off is terrible code. It has a long history going back to 1970s era fortran. Starting fresh is probably preferable
That code is also hyper-optimized for performance. I sincerely doubt you are going to match the performance easily with any random rewrite.
Now, if you had a very clear idea of why the code was making assumptions from the 1990s that are no longer valid, then you might stand a chance of producing something that would outperform it. Or, perhaps, if you had particular knowledge of modern high-performance numerical libraries that you could apply to the problem, then you might be able to beat it.
However, circuit simulation is remarkably difficult to get right (stiff systems with multiple time constants are not uncommon) and generally resistant to parallelization (each device can have its own model which are a unique set of linear differential equations).
If, however, the legacy of ngspice bugs you that much, go look at Xyce and see if that is more to your taste.
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> and generally resistant to parallelization (each device can have its own model which are a unique set of linear differential equations).
Solving sets of differential equations is something that's parallelizable though
See for example how there's physics engines running on GPU. That's mechanics and not electric circuits, however it's differential equations all the same.
> That code is also hyper-optimized for performance. I sincerely doubt you are going to match the performance easily with any random rewrite.
Hyper optimized for '70s era fortran not gonna be all that optimized on modern CPUs.
I bet that just compiler optimizations that LLVM could do with clean code gonna be faster
> Now, if you had a very clear idea of why the code was making assumptions from the 1990s that are no longer valid, then you might stand a chance of producing something that would outperform it. Or, perhaps, if you had particular knowledge of modern high-performance numerical libraries that you could apply to the problem, then you might be able to beat it.
But that's exactly the sort of exotic domain knowledge that AI models have that I don't.
That code was optimized for performance for 1980s hardware. It’s very far from optimized for modern CPUs.
and correctness too - I guess there aren't that many hardcore electrical engineers/physicists/mathematicians that can make sure the results it makes are correct and sound, and debug weird issues coming from numerical stability.
The sort of people who can do this are very rare, and it's not likely they will just randomly decide to donate their time to rewrite the codebase.