官方默认的系统版本有点低，升级一下

Mars
1
  1. 更新一下 source.list
user@starfive:~$ cat /etc/apt/sources.list
#deb https://snapshot.debian.org/archive/debian-ports/20221225T084846Z unstable main
deb https://snapshot.debian.org/archive/debian-ports/20230724T141507Z unstable main
  1. 下载证书
    wget http://ftp.de.debian.org/debian/pool/main/d/debian-ports-archive-keyring/debian-ports-archive-keyring_2024.02.02_all.deb
    sudo dpkg -i debian-ports-archive-keyring_2024.02.02_all.deb
  1. update
sudo apt-get update -y
  1. 可以升级了
sudo apt-get upgrade -y
  1. 完成
user@starfive:~$ cat /etc/os-release 
PRETTY_NAME="Debian GNU/Linux trixie/sid"
NAME="Debian GNU/Linux"
VERSION_CODENAME=trixie
ID=debian
HOME_URL="https://www.debian.org/"
SUPPORT_URL="https://www.debian.org/support"
BUG_REPORT_URL="https://bugs.debian.org/"
2

1.安装开发环境

sudo apt install build-essential cmake
  1. 安装各种的模块
sudo apt-get install -y libarmadillo-dev libarmadillo11
sudo apt-get install -y libensmallen-dev
sudo apt-get install -y cereal  libcereal-dev
  1. 安装 mlpack
    详细信息来看这儿： GitHub - mlpack/mlpack: mlpack: a fast, header-only C++ machine learning library
sudo apt-get install -y libmlpack-dev mlpack-bin
  1. 写一个测试的代码
user@starfive:/opt/work$ cat my_program.cpp 
// This is an interactive demo, so feel free to change the code and click the 'Run' button.

// This simple program uses the mlpack::neighbor::NeighborSearch object
// to find the nearest neighbor of each point in a dataset using the L1 metric,
// and then print the index of the neighbor and the distance of it to stdout.

#include <mlpack.hpp>

using namespace mlpack;

int main()
{
  // Load the data from data.csv (hard-coded).  Use CLI for simple command-line
  // parameter handling.
  arma::mat data("0.339406815,0.843176636,0.472701471; \
                  0.212587646,0.351174901,0.81056695;  \
                  0.160147626,0.255047893,0.04072469;  \
                  0.564535197,0.943435462,0.597070812"); 
  data = data.t(); 

  // Use templates to specify that we want a NeighborSearch object which uses
  // the Manhattan distance.
  NeighborSearch<NearestNeighborSort, ManhattanDistance> nn(data);

  // Create the object we will store the nearest neighbors in.
  arma::Mat<size_t> neighbors;
  arma::mat distances; // We need to store the distance too.

  // Compute the neighbors.
  nn.Search(1, neighbors, distances);

  // Write each neighbor and distance using Log.
  for (size_t i = 0; i < neighbors.n_elem; ++i)
  {
    std::cout << "Nearest neighbor of point " << i << " is point "
        << neighbors[i] << " and the distance is " << distances[i] << "." << std::endl;
  }

  return 0;
}

5.编译 { 速度是有点慢 }

user@starfive:/opt/work$ time g++ -O3 -std=c++14 -o my_program my_program.cpp -larmadillo -fopenmp

real	1m8.549s
user	1m6.585s
sys	0m1.878s
  1. 看看结果
user@starfive:/opt/work$ ./my_program 
Nearest neighbor of point 0 is point 3 and the distance is 0.449757.
Nearest neighbor of point 1 is point 2 and the distance is 0.918409.
Nearest neighbor of point 2 is point 1 and the distance is 0.918409.
Nearest neighbor of point 3 is point 0 and the distance is 0.449757.