Normalize symmetry in multiplication #14
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RyanGlScott
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This bumps the `aig` submodule to bring in the changes from GaloisInc/aig#14, which changes how `aig` performs multiplication to swap the order of arguments if the first argument is a constant. This is because the algorithm that `mul` uses to compute multiplication is biased in its order of arguments, and having the second argument be a constant produces a network with more full adders, which is generally more beneficial. I have added a test case to check to see if the test case from #1828 now produces identical AIGs regardless of the order of arguments. Fixes #1828.
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`mul` will now flip the order of arguments in `mul` if it detects that the second argument is a constant, as this can produce more desirable AIGs if the other argument is symbolic. This is part of an eventual fix for GaloisInc/saw-script#1828.
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RyanGlScott
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Mar 9, 2023
This bumps the `aig` submodule to bring in the changes from GaloisInc/aig#14, which changes how `aig` performs multiplication to swap the order of arguments if the second argument is a constant. This has two benefits: * This ensures that `write_aig` will produce the same networks for `X * C` and `C * X`, where `C` is a constant and `X` is a variable. * The algorithm that `mul` uses to compute multiplication is biased in its order of arguments, and having the first argument be a constant tends to produce networks that ABC has an easier time verifying. (The FFS example under `doc/tutorial/code/ffs.c` is a notable example of this.) I have added a test case to check to see if the test case from #1828 now produces identical AIGs regardless of the order of arguments. Fixes #1828.
RyanGlScott
added a commit
to GaloisInc/saw-script
that referenced
this pull request
Mar 9, 2023
This bumps the `aig` submodule to bring in the changes from GaloisInc/aig#14, which changes how `aig` performs multiplication to swap the order of arguments if the second argument is a constant. This has two benefits: * This ensures that `write_aig` will produce the same networks for `X * C` and `C * X`, where `C` is a constant and `X` is a variable. * The algorithm that `mul` uses to compute multiplication is biased in its order of arguments, and having the first argument be a constant tends to produce networks that ABC has an easier time verifying. (The FFS example under `doc/tutorial/code/ffs.c` is a notable example of this.) I have added a test case to check to see if the test case from #1828 now produces identical AIGs regardless of the order of arguments. Fixes #1828.
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mulwill now flip the order of arguments inmulif it detects that the second argument is a constant, as this can produce more desirable AIGs if the other argument is symbolic. This is part of an eventual fix for GaloisInc/saw-script#1828.