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Example usage of the LAPACK module in Chapel.

This particular file demonstrates how to use the gesv procedure with Chapel's arrays. The gesv procedure solves A*X = B for X given both A and B, where A is a square matrix.

Here, we create A and X, then compute B with a matrix multiplication, and show that the result of the gesv procedure is the same as our synthesized X array (within a small margin of error for floating point).

To compile a program with LAPACK, you may need to add some additional flags depending on how LAPACK was installed on your system:


See the LAPACK module documentation for more information on compiling.

Start by using the LAPACK module to gain access to the gesv function. The Random module will be used to fill arrays with random values.

use Random;
Here we set up several config consts that represent, in order:
  • N, the dimension for the square array A
  • K, the second dimension for arrays X and B
  • epsilon, the margin of error for success
  • seed, a seed for random number generation
config const N = 2;
config const K = 1;
config const epsilon = 1e-13;
config const seed = 41;

Create the arrays A, X, and B. Fill A and X with random values.

var A : [1..N, 1..N] real;
fillRandom(A, seed);

var X : [1..N, 1..K] real;
fillRandom(X, seed);

var B : [1..N, 1..K] real;

Matrix multiply A*X, store result in B

for i in 1..N do
  for j in 1..K do
    for k in 1..N do
      B[i,j] += A[i,k] * X[k,j];

writeln("Matrix A:\n", A, "\n");
writeln("Matrix X:\n", X, "\n");
writeln("Matrix B:\n", B, "\n");

Copy original arrays into temporary arrays.

Input and work array. Becomes garbage.

var WorkA = A;

Input and output. Becomes result of solution (X)

var WorkBX = B;

Output array. Stores pivot indices

var ipiv : [1..N] c_int;

Call the gesv function to solve for X. Note that Chapel arrays are row-major order by default.

var info = gesv(lapack_memory_order.row_major, WorkA, ipiv, WorkBX);

LAPACK returns an error code to indicate a failure.

if info != 0 {
  writeln("There was an error!");
  if info < 0 {
    writeln("Argument ", -info, " was incorrect.");
  } else {
    writeln("The matrix A is a singular matrix. U", (info,info), " is zero");

writeln("gesv result for X:\n", WorkBX, "\n");

The arrays may not be identical due to floating point errors. Use a small value as a margin of error to measure success.

const closeEnough = && reduce [d in (WorkBX - X)] abs(d) < epsilon;

if closeEnough then