lapack

Building opencv 3.1 on windows - where do I specify the LAPACK library location?

由 99封情书 提交于 2021-02-07 23:25:54
问题 For building opencv 3.1 I'm using cmake with Visual Studio 2013. I downloaded the dependencies as shown here: http://docs.opencv.org/3.1.0/d3/d52/tutorial_windows_install.html While configuring cmake, the first thing it shows is: FP16: Compiler support is available A library with BLAS API not found. Please specify library location. LAPACK requires BLAS A library with LAPACK API not found. Please specify library location. The problem is, that I don't know how to specify the location. For the

Building opencv 3.1 on windows - where do I specify the LAPACK library location?

由 假装没事ソ 提交于 2021-02-07 23:24:27
问题 For building opencv 3.1 I'm using cmake with Visual Studio 2013. I downloaded the dependencies as shown here: http://docs.opencv.org/3.1.0/d3/d52/tutorial_windows_install.html While configuring cmake, the first thing it shows is: FP16: Compiler support is available A library with BLAS API not found. Please specify library location. LAPACK requires BLAS A library with LAPACK API not found. Please specify library location. The problem is, that I don't know how to specify the location. For the

BLAS equivalent of a LAPACK function for GPUs

由 半城伤御伤魂 提交于 2021-02-07 15:17:26
问题 In LAPACK there is this function for diagonalization SUBROUTINE DSPGVX( ITYPE, JOBZ, RANGE, UPLO, N, AP, BP, VL, VU, $ IL, IU, ABSTOL, M, W, Z, LDZ, WORK, IWORK, $ IFAIL, INFO ) * I am looking for its GPU implementation. I am trying to find whether this function has been already implemented in CUDA (or OpenCL), but have only found CULA, which is not open source. Therefore and side CUBLAS exists, I wonder how could I know whether a BLAS or CUBLAS equivalent of this subroutine is available. 回答1

Armadillo + BLAS + LAPACK

由 徘徊边缘 提交于 2021-01-29 12:31:23
问题 I am using the armadillo library inside a package (LAMMPS package). I also used Armadillo to compile different codes, and it works fines, and I use the following compiling command: g++ example2.cpp -o example2 -O3 -larmadillo -DARMA_DONT_USE_WRAPPER -lblas -llapack Armadillo works fine for matrix storage and loading inside the package, however, when it comes to matrix-vector multiplication, it gives me the following error: /usr/include/armadillo_bits/wrapper_blas.hpp:42: undefined reference

Cannot link the BLAS from Accelerate Framework during compilation -OS Yosemite 10.0.5

由 百般思念 提交于 2021-01-28 01:59:15
问题 I created a matrix multiplicity code for an assignment but could not get the function working, so I suspect it is the BLAS lib not linked properly. In OS X, the BLAS has been built into the Accelerate Framework, so in makefile I linked the lib by -framework Accelerate and in cpp I also include the header by #include<Accelerate/Accelerate.h> During compilation, my error is: Undefined symbols for architecture x86_64: "dgemm_(char*, char*, int*, int*, int*, double*, double*, int*, double*, int*,

r msm BLAS/LAPACK routine 'DGEBAL' gave error code -3

由 筅森魡賤 提交于 2021-01-27 19:57:02
问题 I'm trying to make a basic markov model using the package msm and things were working fine until I've suddenly started receiving the following error code. I don't know why it's suddenly started throwing this as it was working fine earlier, and I don't think I've changed anything. The error code seems to be pointing to the linear algebra library but I don't know what to do with it exactly ... Error in balance(baP$z, "S") : BLAS/LAPACK routine 'DGEBAL' gave error code -3 The code is as follows:

Levmar:Levenberg-Marquardt非线性最小二乘算法

由 ◇◆丶佛笑我妖孽 提交于 2020-12-11 07:46:54
Levmar:Levenberg-Marquardt非线性最小二乘算法 eryar@163.com Abstract. Levmar is GPL native ANSI C implementations of the Levenberg-Marquardt optimization algorithm.The blog focus on the compilation of levmar on Windows with Visual Studio. Key Words. Levmar, C, LM least squares 1. levmar简介 Gauss-Newton算法是一个古老的处理非线性最小二乘问题的方法。该方法在迭代过程中要求矩阵J(x)满秩。为了克服这个困难，Levenberg(1944)提出了一种新的方法，但未受到重视。后来Marquardt(1963)又重新提出，并在理论上进行了控讨，得到Levenberg-Marquardt方法，简称LM方法。在此基础上，Fletcher(1971)对其实现策略进行了改进，得到了Levenberg-Marquardt-Fletcher方法（LMF）。再后来，More(1978)将LM方法与信赖域方法结合，建立了带信赖域的LM方法。 LM算法的产生主要是解决曲线最小二乘拟合问题

Why does not ldd output the libraries that I have linked when generating the executable file?

由 只谈情不闲聊 提交于 2020-12-06 05:42:20
问题 I have linked the project with ATLAS library, -llapack -lf77blas -lcblas -latlas -lgfortran , and it could compile successfully. But when I use the ldd command to view the dependency libraries, the output is as follows: ubuntu@ubuntu-desktop:~/Desktop/qt_output$ldd test_atlas linux-vdso.so.1 => (0x00007fffa99ff000) libopencv_core.so.2.4 => /home/ubuntu/Documents/3rdparty/lib/libopencv_core.so.2.4 (0x00007fe0577d7000) libgfortran.so.3 => /usr/lib/x86_64-linux-gnu/libgfortran.so.3

Why does not ldd output the libraries that I have linked when generating the executable file?

由 為{幸葍}努か 提交于 2020-12-06 05:41:17
问题 I have linked the project with ATLAS library, -llapack -lf77blas -lcblas -latlas -lgfortran , and it could compile successfully. But when I use the ldd command to view the dependency libraries, the output is as follows: ubuntu@ubuntu-desktop:~/Desktop/qt_output$ldd test_atlas linux-vdso.so.1 => (0x00007fffa99ff000) libopencv_core.so.2.4 => /home/ubuntu/Documents/3rdparty/lib/libopencv_core.so.2.4 (0x00007fe0577d7000) libgfortran.so.3 => /usr/lib/x86_64-linux-gnu/libgfortran.so.3

optim c++优化库配置(windows环境，mingw)

由 [亡魂溺海] 提交于 2020-10-02 21:13:50
optim c++优化库配置(windows环境，mingw) windows环境下做科学计算常用的库是blas,lapack,openblas等，这些和矩阵运算有关，代码也是经过高度优化，下面介绍一个轻量的c++版本优化库optim在win环境下的安装使用方法，如果是linux的话可以用包管理器安装依赖，方便很多，这里就不做介绍了。 预备软件: mingw 730(笔者将qt5自带的设置为系统全局gcc/g++环境),cmder/git bash(提供linux环境，方便执行),cmake(编译lapack使用)，armadillo编译安装(可以先编译安装openblas)，Eigen下载安装(其实只需要头文件即可); OpenBlas源码编译安装（https://www.openblas.net/） 下载openblas源码，解压，打开cmder终端，执行： mkdir build cd build cmake -G "MinGW Makefiles" .. cmake-gui .. #使用图形化命令查看编译选项，勾选DYNAMIC_ARCH,可以生成对芯片架构进行指令优化；天天Entry：BUILD_SHARED_LIBS，生成动态链接库 cmake --build . -j 4. #新版cmake已经支持编译命令了 cmake --install . #默认安装至"C:
订阅 lapack