ghj
Joined 6 years ago
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634
Submissions
83
Member since
May 28
Recent submissions
Comment · 2 years ago
That's crazy high isn't it? That's 1 out of 250 people!
Comment · 2 years ago
Will you still be working on educational content on the side? (e.g. updating fast.ai and/or making one off lectures like https://www.youtube.com/watch?v=jkrNMKz9pWU)
Either way thank you for all the amazing free content you've already put out and good luck on the new endeavor!
Comment · 2 years ago
AdamantChicken2 (aka AlphaCode2) replied to the thread! https://codeforces.com/blog/entry/123035?#comment-1091379
Comment · 2 years ago
Some people on codeforces (the competitive programming platform that this was tested on) are discussing the model: https://codeforces.com/blog/entry/123035
Seems like they don't believe that it solved the 3200 rated problem (https://codeforces.com/contest/1810/problem/G) w/o data leakage
For context, there are only around 20 humans above 3200 rating in the world. During the contest, there were only 21 successful submissions from 25k participants for that problem.
Comment · 2 years ago
I remember deciding that I never want to ever have my DNA in any database after watching this talk:
DEF CON 25 - John Sotos - Genetic Diseases to Guide Digital Hacks of the Human Genome (2017): https://www.youtube.com/watch?v=HKQDSgBHPfY
Comment · 3 years ago
I didn't realize who this was by the title, but this is betaveros, the guy who won 1st place in Advent of Code every single year since 2019:
https://clist.by/account/32289/resource/adventofcode.com/
Comment · 3 years ago
Copying from an older comment of mine shilling Pypy https://news.ycombinator.com/item?id=25595590
PyPy is pretty well stress-tested by the competitive programming community.
https://codeforces.com/contests has around 20-30k participants per contest, with contests happening roughly twice a week. I would say around 10% of them use python, with the vast majority choosing pypy over cpython.
I would guesstimate at least 100k lines of pypy is written per week just from these contests. This covers virtually every textbook algorithm you can think of and were automatically graded for correctness/speed/memory. Note that there's no special time multiplier for choosing a slower language, so if you're not within 2x the speed of the equivalent C++, your solution won't pass! (hence the popularity of pypy over cpython)
The sheer volume of advanced algorithms executed in pypy gives me huge amount of confidence in it. There was only one instance where I remember a contestant running into a bug with the jit, but it was fixed within a few days after being reported: https://codeforces.com/blog/entry/82329?#comment-693711 https://foss.heptapod.net/pypy/pypy/-/issues/3297.
New edit from that previous comment: there's now a Legendary Grandmaster (ELO rating > 3000, ranking 33 out of hundreds of thousands) who almost exclusively use pypy: https://codeforces.com/submissions/conqueror_of_tourist
Comment · 5 years ago
I've commented about this before, but their supposedly optimized implementation is still garbage:
https://news.ycombinator.com/item?id=24125312
There's no reason to build the repeats up by doubling since the string concatenation of two same string is still linear time.
Comment · 5 years ago
PyPy is easily 10x faster than CPython at numeric stuff, which is 99% of these contest problems.
For example, using CPython, if you try to make an array of a million ints, you won't get `int[1000000]` in your memory layout. Each int would actually be an object, which is huge and inefficient to reference (they are something like 24+ bytes each).
PyPy on the other hand, works as expected.
I think the more important point is that PyPy when written like C code, can actually get within 2x of the performance of C code. If it's any slower, python won't be a viable language in competitive programming at all.
(CPython is sometimes still used on other platforms like atcoder.jp, but only because they allow third party libraries like numba and numpy which can fill the same role pypy does)
Comment · 5 years ago
If you want more examples of real world use cases, PyPy is pretty stress-tested by the competitive programming community already.
https://codeforces.com/contests has around 20-30k participants per contest, with contests happening roughly twice a week. I would say around 10% of them use python, with the vast majority choosing pypy over cpython.
I would guesstimate at least 100k lines of pypy is written per week just from these contests. This covers virtually every textbook algorithm you can think of and were automatically graded for correctness/speed/memory. Note that there's no special time multiplier for choosing a slower language, so if you're not within 2x the speed of the equivalent C++, your solution won't pass! (hence the popularity of pypy over cpython)
The sheer volume of advanced algorithms executed in pypy gives me huge amount of confidence in it. There was only one instance where I remember a contestant running into a bug with the jit, but it was fixed within a few days after being reported: https://codeforces.com/blog/entry/82329?#comment-693711 https://foss.heptapod.net/pypy/pypy/-/issues/3297.
Comment · 6 years ago
Isn't this use case the scientific computing use case? That's a fairly large part of the ecosystem to give up on!
I think it's still a relatively low effort way (just need to write a scraper) to create a benchmark on a diverse set of algorithmic tasks that have clearcut criteria on AC/TLE/WA. PyPy is often 10x faster than cpython on these problems (and just 2x slower than equivalent C++ solution) so it will be a much nicer headline too if you can achieve similar performances!
Though I can also see how it can be completely irrelevant for server workloads. Pypy's unicode is so slow, some people on codeforces still use pypy2 over pypy3 just to avoid it. And c extensions is so bad on pypy, you can often get better performance on cpython if you need to use numpy.
Comment · 6 years ago
I stalked the author's linkedin and notice he has competitive programming experience:
https://www.topcoder.com/members/kmod/details/?track=DATA_SC...
(and top 15 putnam, ICPC world finals, etc)
I wonder if he would be interested in optimizing for purely algorithmic tasks?
There are a lot active and successful CPython and PyPy users on https://atcoder.jp/. For example:
https://atcoder.jp/contests/practice2/submissions?f.Task=&f.... (the user "maspy" is rated at 2750 using only cpython!!!)
https://atcoder.jp/contests/practice2/submissions?f.Task=&f.... (though pypy is more practical)
I am linking to atcoder because their testing data is public so you can rerun contestants solutions using both pyston/cpython/pypy for benchmarking purposes: https://www.dropbox.com/sh/arnpe0ef5wds8cv/AAAk_SECQ2Nc6SVGi...
Right now, other than a handful of people who figured out how to make numba's jit work, only pypy is viable for competitive programming. I wonder if you can do better than pypy?
There are also a few red coders on codeforces.com who mostly use pypy (cpython is completely unviable there because numpy and numba is not installed)
https://codeforces.com/submissions/pajenegod
https://codeforces.com/submissions/conqueror_of_tourist
But codeforces' test cases aren't public anyway so it's not as relevant.
Comment · 6 years ago
Soap film is also used to solve the steiner problem: https://www.youtube.com/watch?v=dAyDi1aa40E