cfbolz changed the topic of #pypy to: #pypy PyPy, the flexible snake | IRC logs: and | hacking on TLS is fun, way more fun than arguing over petty shit, turns out
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<marky1991> i'm doing some silly programming problems this year and I was testing one of my solutions with larger and larger Ns to see how it scaled
<marky1991> one thing I've found is that my latest solution has a performance cliff it falls off if I make my iteration count too large
<marky1991> if i remove the final 0 in line 13, the program runs in a second or so
<marky1991> but if i just run this as is, it takes more than 90 seconds, probably more. I killed it when I got impatient. I'll give it more time now
<marky1991> but I'm wondering why it scales soo poorly at that value, the implementation seems like it should be roughly constant time
<marky1991> i also tested it with cpython and get the same huge slowdown at the same value, so I'm guessing that there's something wrong with my algorithm
<marky1991> but I was wondering if anyone else saw what I'm doing wrong
<marky1991> feel free to ignore if it's not interesting, it's obviously not real production code anywhere, so not that important
<cfbolz> marky1991: isn't that because at some point you switch to long integers
<cfbolz> the result grows exponentially
<cfbolz> and at some point the answer doesn't fit into 64 bits any more
<marky1991> hm, it had grown to large integers before that
<marky1991> but that makes some sense
<cfbolz> ok, but it gets slower and slower to add them
<marky1991> right
<marky1991> maybe it finally went past some specific size that just kills it
<cfbolz> marky1991: maybe plot the time?
<cfbolz> marky1991: this is my code for the same problem, looks exponential as expected
<marky1991> it looks like pypy is much faster than cpython for this value, so I guess that's still good
<marky1991> still waiting on cpython to finish
<marky1991> pypy took 75s wall time
<marky1991> but that's surprising, I would expect them to take roughly te same time if the problem were 8 really-big-bignums
<cfbolz> marky1991: we have different bignum implementations
<marky1991> oof, 5m for cpython
<marky1991> ah, ok
<marky1991> thanks for the explanation
<marky1991> i wonder how decimal would perform, will test
<cfbolz> decimal would only help if printing was the problem (unlikely)
<cfbolz> you could try gmpy
<marky1991> my gut feeling was that it would be slower
<cfbolz> nope, factor 4 faster for me
<cfbolz> marky1991: you should switch to using a list instead of a dict though, that helps cpython
<cfbolz> marky1991: here's my slightly weird approach, btw:
<marky1991> rurprising, my implementatoin took longer than 5m if i replaced it with decimal objects
<marky1991> ha, floats just don't work, returning a nan
<marky1991> must exceed the limit
<marky1991> interesting, very different
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<marky1991> the index trick is very clever
<marky1991> much cheaper than my lazy dict-shuffling approach
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