I'm trying to implement a Cholesky decomposition in Halide. Part of common algorithm such as crout consists of an iteration over a triangular matrix. In a way that, the diagonal elements of the decomposition are computed by subtracting a partial column sum from the diagonal element of the input matrix. Column sum is calculated over squared elements of a triangular part of the input matrix, excluding the diagonal element.
Using BLAS the code would in C++ look as follows:
double* a; /* input matrix */
int n; /* dimension */
const int c__1 = 1;
const double c_b12 = 1.;
const double c_b10 = -1.;
for (int j = 0; j < n; ++j) {
double ajj = a[j + j * n] - ddot(&j, &a[j + n], &n, &a[j + n], &n);
ajj = sqrt(ajj);
a[j + j * n] = ajj;
if (j < n) {
int i__2 = n - j;
dgemv("No transpose", &i__2, &j, &c_b10, &a[j + 1 + n], &n, &a[j + n], &b, &c_b12, &a[j + 1 + j * n], &c__1);
double d__1 = 1. / ajj;
dscal(&i__2, &d__1, &a[j + 1 + j * n], &c__1);
}
}
My question is if a pattern like this is in general expressible by Halide? And if so, how would it look like?