Modia.jl
Verilog.jl
Modia.jl | Verilog.jl | |
---|---|---|
4 | 2 | |
318 | 46 | |
0.6% | - | |
6.7 | 0.0 | |
6 months ago | about 7 years ago | |
Julia | Julia | |
MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Modia.jl
-
An open source, educational, low-cost modern analog computer
For circuits a lot of them are represented by differential-algebraic equations (DAEs) and require modeling tools in order to handle the high differential index of the systems. This is the reason why they are typically handled via acausal modeling systems which can do index reduction. For Julia, this is the ModelingToolkit portion of the SciML ecosystem (https://docs.sciml.ai/ModelingToolkit/stable/), and some modeling tools like https://github.com/ModiaSim/Modia.jl and OpenModelica front-ends https://github.com/OpenModelica/OMJulia.jl.
-
‘Machine Scientists’ Distill the Laws of Physics from Raw Data
The thing to watch in the space of Simulink/Modelica is https://github.com/SciML/ModelingToolkit.jl . It's an acausal modeling system similar to Modelica (though extended to things like SDEs, PDEs, and nonlinear optimization), and has a standard library (https://github.com/SciML/ModelingToolkitStandardLibrary.jl) similar to the MSL. There's still a lot to do, but it's pretty functional at this point. The two other projects to watch are FunctionalModels.jl (https://github.com/tshort/FunctionalModels.jl, which is the renamed Sims.jl), which is built using ModelingToolkit.jl and puts a more functional interface on it. Then there's Modia.jl (https://github.com/ModiaSim/Modia.jl) which had a complete rewrite not too long ago, and in its new form it's fairly similar to ModelingToolkit.jl and the differences are more in the details. For causal modeling similar to Simulink, there's Causal.jl (https://github.com/zekeriyasari/Causal.jl) which is fairly feature-complete, though I think a lot of people these days are going towards acausal modeling instead so flipping Simulink -> acausal, and in that transition picking up Julia, is what I think is the most likely direction (and given MTK has gotten 40,000 downloads in the last year, I think there's good data backing it up).
And quick mention to bring it back to the main thread here, the DataDrivenDiffEq symbolic regression API gives back Symbolics.jl/ModelingToolkit.jl objects, meaning that the learned equations can be put directly into the simulation tools or composed with other physical models. We're really trying to marry this process modeling and engineering world with these "newer" AI tools.
-
Julia Receives DARPA Award to Accelerate Electronics Simulation by 1,000x
Maybe of interest in that context:
https://github.com/ModiaSim/Modia.jl
The authors of that tool have a strong background in modeling and simulation of differential algebraic equations. Not so much in designing DSLs, though, so there maybe some technical oddities. But I expect the simulation aspect to be quite decent.
Verilog.jl
-
Compiling Code into Silicon
It doesn't have to be. I once made a julia->verilog transpiler that even recompiled your julia functions with verilator, so you could verify that the code was correct.
https://github.com/interplanetary-robot/Verilog.jl
Of course, gaining traction on something like this is tricky.
I actually think Erlang/BEAM would be a great choice for making EDA tools, because it has concurrent execution model that you could probably very easily make play nice in rudimentary simulations of circuits that have triggers (`always @` sort of stuff.
-
Julia Receives DARPA Award to Accelerate Electronics Simulation by 1,000x
A long long long time ago, I wrote this (currently very unmaintained) julia project, don't know if this is useful to you, but it's pretty clear that there is a LOT of potential for julia in this domain: https://github.com/interplanetary-robot/Verilog.jl
What are some alternatives?
svls - SystemVerilog language server
skywater-pdk - Open source process design kit for usage with SkyWater Technology Foundry's 130nm node.
Automa.jl - A julia code generator for regular expressions
Octavian.jl - Multi-threaded BLAS-like library that provides pure Julia matrix multiplication
ModelingToolkitStandardLibrary.jl - A standard library of components to model the world and beyond
openlane - OpenLane is an automated RTL to GDSII flow based on several components including OpenROAD, Yosys, Magic, Netgen and custom methodology scripts for design exploration and optimization.
Causal.jl - Causal.jl - A modeling and simulation framework adopting causal modeling approach.
PySR - High-Performance Symbolic Regression in Python and Julia
FunctionalModels.jl - Equation-based modeling and simulations in Julia
freepdk-45nm - ASIC Design Kit for FreePDK45 + Nangate for use with mflowgen