On Tue, May 7, 2013 at 6:54 PM, Richard Tew <[email protected]> wrote: > On Wed, May 8, 2013 at 8:17 AM, Bin Huang <[email protected]> wrote: >> Hi Richard, >> >> So I was able to compile with STACKLESS_OFF and manual removal of >> 'static'. I measured the performance again: >> >> Problem size CPython Stackless Stackless_off >> 256x256 14.106 ms 39.331 ms 39.394 ms >> 512x512 110.648 ms 346.857 ms 350.049 ms >> 1024x1024 1022.090 ms 8949.712 ms 8926.275 ms >> 2048x2048 7795.782 ms 80161.503 ms 78647.046 ms >> >> Then I obtained the source code for official Python 2.7.2 tarball >> release and repeated the >> process. Freshly installed Python 2.7.2 also showed slowdown. Clearly, >> it is how >> to install stackless Python and Numpy that matters. > > Okay, if I understand you correctly, you tested official Python 2.7.2 > tarball, and it was similar to the numbers for Stackless_off? The > official Python 2.7.2 tarball is not the cpython column, right?
That's correct. The CPython column I listed was the default Python installation on my machine. And in fact its version is 2.7.3. > > If this is the case, that any straight download and compilation of the > Python source code (whether Stackless or not) gives you similar slow > numbers, then there's something special about whatever gave the > numbers for cpython. > >> Is there anything special that you think I need to pay attention to? > > Yes, the Stackless_off column. Stackless_off is official Python. It > completely compiles out the "Stackless patch" and should give > something that behaves exactly like the official Python with the same > version. So, your official tarball compile should give you the same > numbers as Stackless_off. I like it. I can see that the switch "stackless_off" makes debugging like this much easier. > >> Thanks! > > No, thank you for going to all this work. I expect your cpython is > either 2.7.3, and if so, you should get comparable numbers from the > 2.7.3 stackless source code. Or it is installed from the packaging > system for your operating system and it compiles as 64 bit or > something different. Unless you are going to tell me that I > misunderstood, and that your cpython column was for the official 2.7.2 > tarball, I do not think your problem lies with Stackless. > You just made a good point. So I went ahead and downloaded an official 2.7.3 tarball and repeated the same process. Guess what? Same slowdown happened to official 2.7.3 tarball. > Hope this helps. It really helps. Now I believe the problem is related to how I installed Numpy. I actually had two Numpy installations. One was installed by packaging system (which has superior performance) and the other was by myself manually. It is time to bother Numpy community :-). Cheers, Bin _______________________________________________ Stackless mailing list [email protected] http://www.stackless.com/mailman/listinfo/stackless
