[mlpack-svn] [MLPACK] #206: Building mlpack with VS2010?

[MLPACK Trac]

#206: Building mlpack with VS2010?
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  Reporter:  Adam                 |        Owner:        
      Type:  defect               |       Status:  closed
  Priority:  major                |    Milestone:        
 Component:  mlpack               |   Resolution:  fixed 
  Keywords:  VS2010, Compilation  |     Blocking:        
Blocked By:                       |  
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Changes (by rcurtin):

  * status:  new => closed
  * resolution:  => fixed


Comment:

 Okay.  In r11877 I added a quick CMake rule to look for zlib1.dll and
 iconv.dll and throw a warning if they are not found.  I don't think it's
 the best idea to throw a fatal error there because it's not necessarily a
 strict requirement that libxml2.dll be dynamically linked against
 zlib1.dll and iconv.dll.

 I've also been thinking about DLL placement.  My conclusion is that all of
 the relevant DLLs MLPACK is linked against -- libxml2.dll, zlib1.dll,
 iconv.dll, lapack_win32_MT.dll, and blas_win32_MT.dll -- should be
 "installed on the system", which basically means they should be in
 C:/Windows/System32/ or any of the other directories that are searched for
 DLLs on program load.  It would be particularly tedious to get CMake to
 find all of these DLLs (since it finds the .libs it links against and the
 .dlls may not be right there) and then copy them all to the runtime
 directory.  So, I think it should be up to the user to have all of those
 in the right place.  I'll have to write up a "Windows MLPACK howto" wiki
 page (I'll make a new ticket for that -- it should end up being #212).

 In r11878 I changed Windows linking properties so that LAPACK and BLAS are
 linked against.  Therefore, I think all of the problems you were having
 are solved, and another user could come along and use MLPACK okay.  So, I
 think this ticket is done and I'll resolve it (reopen it if I'm wrong).

-- 
Ticket URL: <https://trac.research.cc.gatech.edu/fastlab/ticket/206#comment:23>
MLPACK <www.fast-lab.org>
MLPACK is an intuitive, fast, and scalable C++ machine learning library developed by the FASTLAB at Georgia Tech under Dr. Alex Gray.