Comments (4)
Hey Gabriel, I can try reproducing myself when I'm back a computer, probably the stencil detection in DaCe programs is somewhat sensitive to the format.
Did you consider writing the JSON directly? It should be fairly straightforward if you program is not humongous 🙂
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Hey Johannes,
Yeah, I've seen the JSON is quite nice and straightforward, but my program is actually quite large. If you could try to reproduce the issue and let me know if what I'm trying to do is currently supported that'd be helpful :).
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I apologize for the wait, I realize it might be too late for you now. I am no longer in academia, so it's hard to find some free time to look into this, and I no longer have access to a machine with an FPGA or with the FPGA tools installed.
It took me a while to get DaCe running, it seems to only work with Python 3.8 and Sympy 1.7, but I finally managed to reproduce your issue.
It's been a long time since I worked with this code, but looking at the code I don't believe sdfg_to_stencilflow.py
is intended to infer/detect stencils; it relies on stencil library nodes already being present in the program. You would need to provide an input SDFG that is already in this form. There is some stencil detection functionality in DaCe, but I think it's risky to rely on this in the general case.
Unfortunately I think the only solution that would reliably give you a representative program with StencilFlow is generating the input JSON files, if not by hand, then somehow scripted.
Keep in mind that the focus of the paper is compiling a stencil DSL; not so much inferring stencils from imperative code in the first place - the code you found is fairly specialized bridge to handle specific stencil programs output by a climate/weather frontend.
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Thank you for taking the time to reproduce the issue @definelicht. It seems the best way to go to take advantage of the optimisations present in StencilFlow is writing the JSON file. This solves the issue :).
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