i am just testing a n_queen solver, yesterday with 2.6.1 vs Nodejs. The code i tested is from https://github.com/chaddotson/puzzles
But pypy is much faster as nqueen grows . And it is 40% faster than nodejs. In smaller numbers < 10 it is slower but it has to do with JIT Warmup right? (pypy-current)~/g/nqueen-benchmark >>> python python_n_queens_solver.py 13 N-Queens Found 73712 Solutions in 94.664358s on a 13x13 board (pypy-current)~/g/nqueen-benchmark >>> pypy python_n_queens_solver.py 13 N-Queens Found 73712 Solutions in 5.488652s on a 13x13 board (pypy-current)~/g/nqueen-benchmark >>> node javascript_n_queens_solver.js 13 ⏎ N-Queens Found 73712 solutions in 7.112s on a 13x13 board On Tue, Sep 1, 2015 at 5:58 PM, Armin Rigo <ar...@tunes.org> wrote: > Hi Dima, > > On Mon, Aug 4, 2014 at 5:04 PM, Dima Tisnek <dim...@gmail.com> wrote: > > Attached is n-queens solver (pardon my naive algorithm), it runs: > > python 2.7.6: 17s > > pypy 2.4.0 alpha: 23s > > same nojit: 32s > > > > I've tried similar-looking algorithm for another problem before, and has > > similar results -- somehow pypy was slower. > > > > feel free to investigate / tweak or even use on speed.pypy.org > > So, it took us more than one year, but now I finally figured it out. > The reason it is slower in PyPy is because sets recompute the items' > hash much more often than in CPython. I fixed it in the branch > 'keys_with_hash' (which is just too late for pypy 2.6.1). Some > microbenchmarks are 2x or 3x faster now. > > In your code, it shows up as the _diff() function, which returns "a - > b" where a and b are sets of complicated objects. Actually, there are > always disjoint sets, so the original code might be a bit buggy :-) > But the _diff() operation is now twice faster. I get the following > times on your nq.py example: > > python 2.7.3: 15.5s > pypy 2.6.1 in keys_with_hash: 10.9s > same with '--jit off': 20.3s > > > A bientôt, > > Armin. > _______________________________________________ > pypy-dev mailing list > pypy-dev@python.org > https://mail.python.org/mailman/listinfo/pypy-dev >
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