Skip to content

Latest commit

 

History

History
 
 

ormqr

Folders and files

NameName
Last commit message
Last commit date

parent directory

..
 
 
 
 
 
 
 
 

cuSOLVER QR factorization dense linear solver example

Description

This code demonstrates a usage of cuSOLVER ormqr function for doing dense QR factorization to solve a linear system

Ax=b

A is a 3x3 dense matrix, nonsingular

A = | 1.0 | 2.0 | 3.0 |
    | 4.0 | 5.0 | 6.0 |
    | 2.0 | 1.0 | 1.0 |

Examples perform following steps for both APIs:

  • A = Q*R by GEQRF
  • B = Q^T*B by ORMQR
  • Solve R*X = B by TRSM

Supported SM Architectures

All GPUs supported by CUDA Toolkit (https://developer.nvidia.com/cuda-gpus)

Supported OSes

Linux
Windows

Supported CPU Architecture

x86_64
ppc64le
arm64-sbsa

CUDA APIs involved

Building (make)

Prerequisites

  • A Linux/Windows system with recent NVIDIA drivers.
  • CMake version 3.18 minimum

Build command on Linux

$ mkdir build
$ cd build
$ cmake ..
$ make

Make sure that CMake finds expected CUDA Toolkit. If that is not the case you can add argument -DCMAKE_CUDA_COMPILER=/path/to/cuda/bin/nvcc to cmake command.

Build command on Windows

$ mkdir build
$ cd build
$ cmake -DCMAKE_GENERATOR_PLATFORM=x64 ..
$ Open cusolver_examples.sln project in Visual Studio and build

Usage

$  ./cusolver_ormqr_example

Sample example output:

A = (matlab base-1)
1.00 2.00 3.00
4.00 5.00 6.00
2.00 1.00 1.00
=====
B = (matlab base-1)
6.00
15.00
4.00
=====
after geqrf: info = 0
after ormqr: info = 0
X = (matlab base-1)
1.00
1.00
1.00