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I am recently recompiling a Linux code on windows with intel fortran compiler (included in the intel parallel composer xe 2013). After 2 months work (replacing some I/O functions and using intel MKL), I think it works fine on windows and I checked the results. But there are some performace issues remained.
In general my question is what would be the option for making a scientific program runs faster ( a program deals with large matrices and solving eigenvalue problems using conjugate grad methods ) on Windows. I used /O3 and some other options. but it still not as fast as I expected.
I made a benchmark between a intel compiled (/nologo /O3 /QaxSSE4.2 /QxSSE4.2 /Qunroll:1000000000 /Qvec-threshold:0 /heap-arrays512 /fpp /warn:interfaces /fp:source /names:lowercase /assume:underscore /ccdefault:none /check:none /libs:dll /threads) serial version of the code and MinGW compiled (-pipe -O3 -funroll-loops -ffast-math) serial version of the code. I compared the time consume of each iteration. intel version takes 400 sec but MinGW version takes 120 sec. That's not what I've seen on linux. In general the speed of intel compiled code is much faster. Accroding to the VTune result ( I am still a beginner of using it ), there is only 2 subroutines in the intel build took most of the time, but the MinGW build took a lot shorter time.
I did NOT change anything of the iteration part since there is no system related things in the iteration part. And I'd like to solve the serial version completely before moving on to a parallel version.
Any ideas?
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