Improvement/field inv pornin20 #106
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
Arya Tabaie seems not to be a GitHub user. You need a GitHub account to be able to sign the CLA. If you have already a GitHub account, please add the email address used for this commit to your account. You have signed the CLA already but the status is still pending? Let us recheck it. |
gbotrel
approved these changes
Dec 6, 2021
| return b | ||
| } | ||
|
|
||
| // Though we're defining k as a constant, this code "profoundly" assumes that the processor is 64 bit |
There was a problem hiding this comment.
"profoundly" assumes --> is optimized ?
There was a problem hiding this comment.
Doesn't make a whole lot of sense. Removing.
| // approximate a big number using its uppermost and lowermost bits | ||
| func approximate(x *{{.ElementName}}, n int) uint64 { | ||
|
|
||
| if n <= 64 { |
There was a problem hiding this comment.
question, just based on the function comment; if say, n == 24, shouldn't this clear the 40 other bits to 0?
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Benchmarked on a VM with an AMD EPYC 7R32 processor
For bw6-761/fp speedup ranged from 71% to 77%.
For bn254/fp speedup ranged from 43% to 65%.
Speedup on my ARM laptop was nowhere near as dramatic.
The inconsistency in the small field performance is due to higher variability in the number of outer loop iterations, a random effect that gets smoothed out in higher field size. In general, the algorithm has a good asymptotic complexity and is expected to scale well.
TODOs:
InverseOldandmulWRegularBf(cleanup)linearCombNonModular,mulWRegular,montReduceSigned) (perf)