gels

hipSOLVER linear least-squares

Description

This example illustrates the use of hipSOLVER's linear least-squares solver, gels. The gels functions solve an overdetermined (or underdetermined) linear system defined by an $m$-by-$n$ matrix $A$, and a corresponding matrix $B$, using the QR factorization computed by geqrf (or the LQ factorization computed by gelqf). The problem solved by this function is of the form $A\times X=B$.

If $m\geq n$, the system is overdetermined and a least-squares solution approximating $X$ is found by minimizing $||B−A\times X||$ (or $||B−A^\prime\times X||$). If $m \text{ \textless}\ n$, the system is underdetermined and a unique solution for X is chosen such that $||X||$ is minimal.

This example shows how $A\times X = B$ is solved for $X$, where $X$ is an $m$-by-$1$ matrix. The result is validated by calculating $A\times X$ for the found result, and comparing that with $B$.

Application flow

1. Parse the user inputs, declare several constants for the sizes of the matrices.
2. Allocate the input- and output matrices on the host and device, initialize the input data.
3. Create a hipSOLVER handle.
4. Query the size of the working space of the gels function and allocate the required amount of device memory.
5. Call the gels function to solve the linear least squares problem: $A\times X=B$.
6. Copy the device result back to the host.
7. Print the status value of the gels function.
8. Free device resources and the hipSOLVER handle.
9. Validate that the result found is correct by calculating $A\times X$, and print the result.

Command line interface

The application provides the following optional command line arguments:

• --n <n>. Number of rows of input matrix $A$, the default value is 3.
• --m <m>. Number of columns of input matrix $A$, the default value is 2.

Key APIs and Concepts

hipSOLVER

• hipSOLVER is initialized by calling hipsolverCreate(hipsolverHandle_t*) and it is terminated by calling hipsolverDestroy(hipsolverHandle_t).

• hipsolver(SS|DD|CC|ZZ)gels solves the system of linear equations defined by $A\times X=B$, where $A$ is an m-by-n matrix, $X$ is an n-by-nrhs matrix, and $B$ is an m-by-nrhs matrix. Depending on the character matched in (SS|DD|CC|ZZ), the solution can be obtained with different precisions:

  • S (single-precision: float).
  • D (double-precision: double).
  • C (single-precision complex: hipFloatComplex).
  • Z (double-precision complex: hipDoubleComplex).

  The gels function also requires the specification of the leading dimension of all matrices. The leading dimension specifies the number of elements between the beginnings of successive matrix vectors. In other fields, this may be referred to as the stride. This concept allows the matrix used in the gels function to be a sub-matrix of a larger one. Since hipSOLVER matrices are stored in column-major order, the leading dimension must be greater than or equal to the number of rows of the matrix.

• hipsolver(SS|DD|CC|ZZ)gels_bufferSize allows to obtain the size needed for the working space for the hipsolver(SS|DD|CC|ZZ)gels function.

Used API surface

hipSOLVER

• hipsolverDDgels
• hipsolverDDgels_bufferSize
• hipsolverHandle_t
• hipsolverCreate
• hipsolverDestroy

HIP runtime

• hipFree
• hipMalloc
• hipMemcpy
• hipMemcpyHostToDevice
• hipMemcpyDeviceToHost