犰狳+ Matlab Mex segfault [英] Armadillo + Matlab Mex segfault

问题描述

我整天都在摆弄，所以我想我可以让每个人都从我的经验中受益，请在下面查看我的答案.

I fiddled with this the whole day, so I thought I might make everyone benefit from my experience, please see my answer below.

我首先遇到了在Matlab中运行已编译的Mex文件的问题，因为Matlab抱怨说它无法打开共享库libarmadillo.我使用环境变量LD_LIBRARY_PATH解决了此问题和LD_RUN_PATH(在osx中​​为DYLD_LIBRARY_PATH和LYLD_RUN_PATH).

I first had a problem with running a compiled Mex file within Matlab, because Matlab complained that it couldn't open the shared library libarmadillo. I solved this using the environment variables LD_LIBRARY_PATH and LD_RUN_PATH (DYLD_LIBRARY_PATH and LYLD_RUN_PATH in osx).

问题仍然存在，即使是完全相同的代码也可以在Matlab外部编译并运行良好(不是Mex'd)，一个简单的测试文件仍会在运行时出现段错误.

The problem remained however, that a simple test file would segfault at runtime even though the exact same code would compile and run fine outside Matlab (not Mex'd).

推荐答案

Segfault似乎是由于Matlab在捆绑的LAPACK和BLAS库中使用64位整数(long long或int64_t)造成的.另一方面，犰狳默认使用32位整数(在64位平台上为常规int或int32_t).

The segfault seems to be caused by the fact that Matlab uses 64bits integers (long long or int64_t) in its bundled LAPACK and BLAS libraries. Armadillo on the other hand, uses 32bits integers (regular int on a 64bits platform, or int32_t) by default.

有两种解决方案；第一个涉及强制Matlab改为链接到系统的库(使用int)，第二个涉及更改Armadillo的配置文件以通过BLAS启用long long.我倾向于认为第一个更可靠，因为没有黑盒效应，但是它也更麻烦，因为您需要手动安装并记住BLAS和LAPACK库的路径.

There are two solutions; the first one involves forcing Matlab to link to the system's libraries instead (which use ints), the second involves changing Armadillo's config file to enable long longs with BLAS. I tend to think that the first is more reliable, because there is no black-box effect, but it's also more troublesome, because you need to manually install and remember the path of your BLAS and LAPACK libs.

两个解决方案都要求我停止使用Armadillo的共享库，并手动链接/包含源. 为此，您只需在系统上安装LAPACK和BLAS(如果尚未安装，在libblas-dev和liblapack-dev的Ubuntu中)，然后将整个includes目录复制到类似$HOME/.local/arma的合理位置即可.例子.

Both solutions required that I stopped using Armadillo's shared libraries and linked/included manually the sources. To do this, you must simply install LAPACK and BLAS on your system (if they are not already there, in Ubuntu that's libblas-dev and liblapack-dev), and copy the entire includes directory somewhere sensible like in $HOME/.local/arma for example.

在matlab控制台中，将环境变量BLAS_VERSION和LAPACK_VERSION设置为指向系统的库.就我而言(Ubuntu 14.04，Matlab R2014b):

From the matlab console, set the environment variables BLAS_VERSION and LAPACK_VERSION to point to your system's libraries. In my case (Ubuntu 14.04, Matlab R2014b):

setenv('BLAS_VERSION','/usr/lib/libblas.so');
setenv('LAPACK_VERSION','/usr/lib/liblapack.so');

然后可以正常编译:

mex -compatibleArrayDims -outdir +mx -L/home/john/.local/arma -llapack -lblas -I/home/john/.local/arma test_arma.cpp

，或者如果您在includes/armadillo_bits/config.hpp中定义标志ARMA_64BIT_WORD，则可以删除选项-compatibleArrayDims.

or if you define the flag ARMA_64BIT_WORD in includes/armadillo_bits/config.hpp, you can drop the option -compatibleArrayDims.

第二种解决方案涉及取消Armadillo的配置文件includes/armadillo_bits/config.hpp中的标志ARMA_BLAS_LONG_LONG的注释. Matlab将链接到其捆绑的LAPACK和BLAS库，但是这次Armadillo不会出现段错误，因为它使用了正确的字长.与以前一样，如果要删除-compatibleArrayDims，也可以取消注释ARMA_64BIT_WORD.

The second solution involves uncommenting the flag ARMA_BLAS_LONG_LONG in Armadillo's config file includes/armadillo_bits/config.hpp. Matlab will link to its bundled LAPACK and BLAS libraries, but this time Armadillo won't segfault because it's using the right word-size. Same than before, you can also uncomment ARMA_64BIT_WORD if you want to drop the -compatibleArrayDims.

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