That's fair. Currently in my eyes it's more of an academic curiosity
currently that i would probably take parts of and program conventionally.
Funny how you mention "black box" because recently there was a news
article about scientists increasingly not understanding why machine
learning is working the way it is with apparent patterns of emergent
behaviour.
Kit
On 10/11/2022 22:17, Sven Barth wrote:
Am 10.11.2022 um 19:10 schrieb J. Gareth Moreton via fpc-devel:
Hi everyone,
This has been something that has been on my mind for a while now, but
with my increasingly more complex optimisations being developed for
the Free Pascal Compiler and the code becoming an ever bigger
spiderweb of conditions, it got me to start wondering... might
compiler optimisation be a candidate for AI? Often I try to
hand-optimise assembly language to get the same output in fewer
cycles (and fewer bytes too if possible), and then see if I can
program the compiler to match it. I can't hope to catch every
possible optimisation though, and I wonder if using an AI in some way
to develop more efficient machine code has ever been a serious
contender for research. I have heard of stories like the Deepmind AI
finding a faster way to multiply matrices, so it seems logical that
it can improve instruction processes.
You still need to feed the model with the necessary rules and with
necessary training data of both correct and incorrect approaches.
But even then *I* wouldn't want to have any of that black box mambo
jumbo in FPC, cause when a bug occurs in the optimizations due to some
decision the model made... well... tough luck. With the current
approach you need to bash your head a bit against the next wall to
find the location of the issue, but with a machine learning approach
(let's not call it AI, cause there's nothing “intelligent” about that)
you can't even do that. You can only fiddle with what you fed into the
model and hope for the best (and wonder why it now fails at a
completely different area).
Regards,
Sven
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