Hi, I've stumbled across a peculiar performance issue with Pypy across some different platforms. It was very visible in some calculation heavy code that I wrote that uses Python's complex number type to calculate the well-known Mandelbrot set.
Pypy running the code on my Windows machine is doing okay, but when running the same code on Pypy on different systems, the performance difference is so big it is not even funny. The other implementations are MUCH faster than the windows one. Which is quite unexpected because the other machines I've tested on have the same or much lower physical CPU specs than the windows machine. Here's the comparison: Machine specs: Windows: 64 bits Windows 7, Intel Core 2 Quad 3.4 Ghz Linux: 32 bits Mint 18, Virtualbox VM on above windows machine Mac mini: OS X 10.11.6, Intel Core 2 Duo 2.53 Ghz The test code I've been using is here: https://gist.github.com/irmen/c6b12b4cf88a6a4fcf5ff721c7089078 Test results: function: mandel / iterations Mac mini, Pypy 5.4.1 (64-bit): 0.81 sec / 0.65 sec Linux, Pypy 5.1 (32-bit): 1.06 sec / 0.64 sec Windows, Pypy 5.4.1 (32-bit): 5.59 sec / 2.87 sec What could cause such a huge difference? Is it perhaps a compiler issue (where gcc/clang are MUCH better at optimizing certain things, although I wonder how much of a factor this is because Pypy is doing JITting by itself as far as I am aware)? Or is something strange going on with the way the complex number type is implemented? (the difference doesn't occur when using only floats) Regards Irmen de Jong -- https://mail.python.org/mailman/listinfo/python-list
