One-sided Jacobi alogirhm is a classic and robust method to calculate Singular Value Decomposition (SVD), which can be applied to any dense matrix with the size of \(M \times N\). In this library, it is denoted as GESVJ, same as the API name used in LAPACK.
\[A = U \Sigma V^T\]
where \(A\) is a dense symmetric matrix of size \(m \times n\), \(U\) is \(m \times m\) matrix with orthonormal columns and and \(V\) is \(n \times n\) matrix with orthonormal columns, and \(\Sigma\) is diagonal matrix. The maximum matrix size supported in FPGA is templated by NRMAX, NCMAX.