使用 apt 源安装 ROCm 6.0.x 在Ubuntu 22.04.01

从源码编译 rocSolver

本人只操作过单个rocm版本的情景，20240218 ubuntu 22.04.01

1，卸载原先的rocm

https://docs.amd.com/en/docs-5.1.3/deploy/linux/os-native/uninstall.html
 

# Uninstall single-version ROCm packages
sudo apt autoremove rocm-core

# Uninstall Kernel-mode Driver
sudo apt autoremove amdgpu-dkms

# remove apt source
sudo rm /etc/apt/sources.list.d/.list
sudo rm /etc/apt/sources.list.d/.list
sudo rm /etc/apt/sources.list.d/rocm.list
sudo rm /etc/apt/sources.list.d/amdgpu.list

sudo rm -rf /var/cache/apt/*
sudo apt-get clean all

sudo reboot

2，安装最新的rocm

https://rocm.docs.amd.com/projects/install-on-linux/en/latest/tutorial/quick-start.html#rocm-install-quick

sudo apt install "linux-headers-$(uname -r)" "linux-modules-extra-$(uname -r)"
# See prerequisites. Adding current user to Video and Render groups
sudo usermod -a -G render,video $LOGNAME
wget https://repo.radeon.com/amdgpu-install/6.0.2/ubuntu/jammy/amdgpu-install_6.0.60002-1_all.deb
sudo apt install ./amdgpu-install_6.0.60002-1_all.deb
sudo apt update
sudo apt install amdgpu-dkms
sudo apt install rocm
sudo reboot
sudo amdgpu-install --usecase=graphics,rocm
sudo reboot

3，安装依赖

Clang: ...  'cmath' file not found
找不到 #include_next

sudo apt install libstdc++-12-dev

4，示例

4.1 amd官方示例

$ git clone --recursive  https://github.com/amd/rocm-examples.git
$ cd HIP-Basic/device_query
$ make
$ ./hip_device_query

4.2 rocsolver_dgeqrf

ex_rocsolver_dgeqrf.cpp

/
// example.cpp source code //
/

#include  // for std::min
#include   // for size_t
#include 
#include 
#include  // for hip functions
#include  // for all the rocsolver C interfaces and type declarations

void init_vector(double* A, int n)
{
  for(int i=0; i hA(size_A);      // creates array for matrix in CPU
  std::vector hIpiv(size_piv); // creates array for householder scalars in CPU

  init_vector(hA.data(), size_A);
  memset(hIpiv.data(), 0, size_piv*sizeof(double));

  print_matrix(hA.data(), M, N, lda);

  double *dA, *dIpiv;
  hipMalloc(&dA, sizeof(double)*size_A);      // allocates memory for matrix in GPU
  hipMalloc(&dIpiv, sizeof(double)*size_piv); // allocates memory for scalars in GPU

  // here is where you would initialize matrix A (array hA) with input data
  // note: matrices must be stored in column major format,
  //       i.e. entry (i,j) should be accessed by hA[i + j*lda]

  // copy data to GPU
  hipMemcpy(dA, hA.data(), sizeof(double)*size_A, hipMemcpyHostToDevice);
  // compute the QR factorization on the GPU
  rocsolver_dgeqrf(handle, M, N, dA, lda, dIpiv);
  // copy the results back to CPU
  hipMemcpy(hA.data(), dA, sizeof(double)*size_A, hipMemcpyDeviceToHost);
  hipMemcpy(hIpiv.data(), dIpiv, sizeof(double)*size_piv, hipMemcpyDeviceToHost);

  printf("\nR =\n");
  print_matrix(hA.data(), M, N, lda);
  printf("\ntau=\n");
  print_matrix(hIpiv.data(), 1, N, 1);

  // the results are now in hA and hIpiv, so you can use them here

  hipFree(dA);                        // de-allocate GPU memory
  hipFree(dIpiv);
  rocblas_destroy_handle(handle);     // destroy handle
}

Makefile:

EXE := ex_rocsolver_dgeqrf

all: $(EXE)

INC :=  -I /opt/rocm/include -D__HIP_PLATFORM_AMD__
LD_FLAGS := -L /opt/rocm/lib -lamdhip64 -lrocblas -lrocsolver

ex_rocsolver_dgeqrf.o: ex_rocsolver_dgeqrf.cpp
        g++ $< $(INC) -c -o $@

ex_rocsolver_dgeqrf: ex_rocsolver_dgeqrf.o
        g++ $< $(LD_FLAGS) -o $@


.PHONY: clean
clean:
        ${RM} *.o $(EXE)

运行效果：

使用matlab对结果做验证：