In this work, we present a new 2D data distribution of a sparse symmetric matrix, which balances the workload and the number of nonzero entries explicitly. We have incorporated low-overhead task-based Cholesky and LDLt algorithms in the symPACK solver using this new distribution, implemented using a custom runtime environment based on the UPC++ communication framework. We analyze the performance achieved during the numerical factorization as well as that of the solution phase.