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User-friendly language for programming efficient simulations

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Re: User-friendly language for programming efficient simulations

#5
It seems like it would be much more straightforward to write a graph-based FEM library for MATLAB than to make an entirely new language around a feature with a very specific and very narrow use case. Still, the high performance aspects of simit seem interesting, assuming that they weren't too badly cherrypicked.

Re: User-friendly language for programming efficient simulations

#6

It seems like it would be much more straightforward to write a graph-based FEM library for MATLAB than to make an entirely new language around a feature with a very specific and very narrow use case. Still, the high performance aspects of simit seem interesting, assuming that they weren't too badly cherrypicked.

Yea, I'm not really sure what a new language buys them here. It seems they could have just released a library (not even tied to Matlab) with their highly tuned stiffness matrix assembly routines and their kernels...

Re: User-friendly language for programming efficient simulations

#8
post #7

It is worth noting that Simit shares an author with Halide: http://halide-lang.org/ I'd say Halide was definitely a success of domain specific high performance language, so hopefully Simit is too.

It actually shares two authors (Jon and Saman). Their work on Halide was amazing!

Re: User-friendly language for programming efficient simulations

#9

It seems like it would be much more straightforward to write a graph-based FEM library for MATLAB than to make an entirely new language around a feature with a very specific and very narrow use case. Still, the high performance aspects of simit seem interesting, assuming that they weren't too badly cherrypicked.

We needed new language constructs (the matrix assembly) and a new type system for matrices that ties back to the graph to make it simple and fast. It is also not limited to FEM codes. It can be used to write any application that computes on sparse systems using linear algebra. Some application areas are optimization, machine learning, data analytics, fluid dynamics, image processing, and robotics.

For more information about the language, why it is designed the way it is, why it is fast, and what applications it can be used for, see the talk I gave at Microsoft Research last Friday: https://youtu.be/raPkxhHy5ro?t=40m32s

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