The progress of convolutional layer verification is abnormally slow #452
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QuestionHi, I recently used ezkl to verify a single convolutional layer and found that the verification speed is very slow. I would like to ask if this is normal. The details are as follows: The model: Get setting.json through
Note that the num_constraints is 3395864 The execution of
The execution of
The execution of I'm wondering why the setup stage is taking such a long time (previously when I was testing constraints of the same or even larger scale using ezkl, it took less time than this model). Is it because convolutional operations occupy more columns, or because of the larger input/output sizes or some other reason? Is there any solution or trick to improve efficiency? Thank you very much! |
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Replies: 1 comment 15 replies
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can you send a sample of the model ? will take a look :) |
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so we have an algo for creating copy constraints which is very memory efficient -- however, because it needs to keep track of ordering the constraints were created in, for a very large number of copy constraints (this is the case with conv layers things), things can get unbearably slow. So it seems like that for this very particular instance -- that algo is no good and the default algorithm in Halo2 is the better choice
ty very much for catching this