Symmetric Matrix Jacobi based Eigen Value Decomposition (SYEVJ)
\[A U = U \Sigma\]
where \(A\) is a dense symmetric matrix of size \(m \times m\), \(U\) is a \(m \times m\) matrix with orthonormal columns, each column of U is the eigenvector \(v_{i}\), and \(\Sigma\) is diagonal matrix, which contains the eigenvalues \(\lambda_{i}\) of matrix A. The maximum matrix size supported in FPGA is templated by NMAX.