macos xcode ide Mac和IOS使用Apple原生BLAS库

Apple官方提供了Accelerate的Libary，并且官方文档中是swift和Object-C的调用，但是事实上，也可以通过C进行native调用。

因为这些库的头文件目录

/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/System/Library/Frameworks/Accelerate.framework/Versions/Current

这里给出一个例子：

#include

#include

#include

#include

template class matrix {

public:

matrix(const size_t& n) : n_(n), data_(n_*n_) {}

T* data() { return data_.data(); }

const T* data() const { return data_.data(); }

std::vector& vec() { return data_; }

size_t const& n() const { return n_; }

const std::vector& vec() const { return data_; }

private:

size_t n_;

std::vector data_;

};

std::random_device rd;

std::mt19937 gen(rd());

std::uniform_real_distribution<> dis(-1.0, 1.0);

template matrix random(const size_t& n) {

matrix m(n);

std::generate_n(m.vec().begin(), m.vec().size(), std::bind(dis, gen));

return m;

}

template std::ostream& operator<<(std::ostream& o, const matrix& m) {

auto const n = m.n();

size_t j = 0;

for (auto const& i : m.vec()) {

o << i <<" ";

if(j++%n == n-1) o << std::endl;

}

return o;

}

int main () {

const size_t n = 4;

matrix A = random(n), B = random(n), C(n);

std::cout << A << std::endl << B << std::endl;

cblas_sgemm(CblasRowMajor, CblasNoTrans, CblasNoTrans, n, n, n,

1.0, A.data(), n, B.data(), n, 0.0, C.data(), n);

std::cout << C << std::endl;

return 0;

}

编译命令

clang++ -O3 -std=c++11 cblas_test.cpp -I/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/System/Library/Frameworks/Accelerate.framework/Versions/Current/Frameworks/vecLib.framework/Headers/ -framework Accelerate -o cblas_tes

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