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Julia receives DARPA award to accelerate electronics simulation

juliacomputing.com

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Re: Julia receives DARPA award to accelerate electronics simulation

#21

Post by oxinabox »

This seems very promising to me One big part of circuit simulation is solving differential equations. That's the whole inducer, resistor, capacitor thing. Julia has hands down the best toolkit for differential equation solving. Most circuit simulators today are going to be using old methods invented in the 60's-80's. Neglecting the state of the art developments.

Someone made a blog post recently comparing the time to simulate with LTSpice vs writng and solving the system in Julia https://klaff.github.io/LTSvDEQ_1.jl.html this is a very simple circuit, and they still got a 100x speed up. Sure that is neglecting the time it takes to actually extract the differnetial equetion from the circuit. But from what i hear that kind of thing is something this DARPA project will be working on. And sure LTSpice isn't state of the art. But still I find this indicative and promising.

Re: Julia receives DARPA award to accelerate electronics simulation

#22

Post by Sukera »

nicolashahn wrote: post #15
meepmorp wrote: post #12

Fix the headline - it should say "Julia Computing Receives DARPA Award to Accelerate Electronics Simulation by 1,000x" The money is going to a company.

Yeah, I think most people on this site are going to first assume the language.

It's also weirdly editorialized, since the original title also says "Julia Computing"

Re: Julia receives DARPA award to accelerate electronics simulation

#23

Post by d33lio »

ultrasounder wrote: post #17
d33lio wrote: post #5

LT-Spice is absolute trash and basically why I decided to leave EE for CS in college... among many other reasons! Essentially, because after learning all kinds of math my linear systems prof basically said "yeah, at some point you just have to simulate everything because the math you learned only applies maybe 60% of the time". Granted, I do not think I was exactly destined to be a great electrical engineer. Electron…

Been using LTSpice for the last decade or so and am just fine simulating everything from Buck to current sense circuits to battery monitoring systems to HBridge. Don’t know what your beef is with LTSpice but still can’t get around the fact you quit your discipline for the lack of a better tool. If you didn’t like what you had to deal with why didn’t you pivot to CS and invent a better simulation tool. Just saying.

I'm really just being cheeky, the writing was on the wall for me about three years in that EE wasn't for me.

Granted, I make a great living writing software and honestly have really benefitted from my 67% complete EE degree. Software ppl generally have zero idea how computers work / how to really leverage hardware bits to accelerate certain workloads. The ideal CS education for me is based in EE but also starts with both lisp and C. NOT Python. However, I was a horribly distracted student throughout college so I really should be the last person giving recs for coursework.

Re: Julia receives DARPA award to accelerate electronics simulation

#25

Post by adgjlsfhk1 »

meepmorp wrote: post #12

Fix the headline - it should say "Julia Computing Receives DARPA Award to Accelerate Electronics Simulation by 1,000x" The money is going to a company.

Note that while Julia Computing and Julia are different entities, the former is the employer of most of the top contributors to Julia. Lots of this grant will probably go into paying for additional features for `DifferentialEquations.jl` or compiler work necessary to speed up some of this code.

Re: Julia receives DARPA award to accelerate electronics simulation

#26

Post by ChrisRackauckas »

vlovich123 wrote: post #20
ChrisRackauckas wrote: post #13

Earlier quoted context omitted.

There are ways to surrogatize portions of a simulation, replacing large portions with ML-trained surrogates. There are already demonstrations in different domains (on highly stiff differential-algebraic equations) showing that you can get these kinds of speedups at around 99% accuracy. https://arxiv.org/abs/2010.04004 https://arxiv.org/abs/2103.05244

> can get these kinds of speedups at around 1% accuracy Shouldn't this be at around "at around 99% accuracy" or "within around 1% accuracy loss"?

Thanks, fixed.

Re: Julia receives DARPA award to accelerate electronics simulation

#28

Post by KenoFischer »

dreamcompiler wrote: post #3

I'm having a lot of trouble understanding how "just add AI" is going to make electronics simulation 1000x faster.

Chris has posted the relevant papers in a sibling comment, but let me try to give an intuitive explanation. Say you have some sort of electronic device like an amplifier. It is made out of many individual transistors and parasitics, but its time evolution is overall guided mostly by the amplifier characteristics its supposed to implement plus boundary effects and corrections from the parasitics. So what you try to do is to learn a simpler system of equations that captures the time evolution plus a (highly-nonlinear, complicated) projection that recovers the signals of interest (if you don't care about reproducing interior signals, you can usually get away with a simpler model). Of course it's not obvious that this should actually work (though of course picking a model of the same size as the system plus an identity projection is always possible, so it'll always work for some size of the model being learned, just at that point you don't get a speedup), but our initial results show that it does seem to be very promising.

Re: Julia receives DARPA award to accelerate electronics simulation

#29

Post by yesenadam »

adgjlsfhk1 wrote: post #25
meepmorp wrote: post #12

Fix the headline - it should say "Julia Computing Receives DARPA Award to Accelerate Electronics Simulation by 1,000x" The money is going to a company.

Note that while Julia Computing and Julia are different entities, the former is the employer of most of the top contributors to Julia. Lots of this grant will probably go into paying for additional features for `DifferentialEquations.jl` or compiler work necessary to speed up some of this code.

Apparently 4 of the 6 founders of Julia Computing are the 4 creators of Julia.

Re: Julia receives DARPA award to accelerate electronics simulation

#30

Post by adgjlsfhk1 »

amelius wrote: post #24

1000x sounds nice, but can you trust the results? Also, why doesn't the funding go to more general linear algebra (and related) solver software, which can then be used in many physics packages?

Note that DifferentialEquations.jl already has bindings for R and Python, so this has the potential to be used in many physics packages.
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