Freelancer Limited secured a USD 510,000 task order for the US Bureau of Reclamation project looking to optimize and speed up the sparse matrix linear equations solver for computational fluid dynamics (CFD) models. The Sedimentation and River Hydraulics Challenge seeks a stable, fast, and parallelizable sparse matrix linear equation solver (numerical algorithm implemented in a subroutine) for typical CFD models. The solver should run on current multi-core personal computers (PCs) with scalable speedup. Typically, to solve this problem, a large-scale linear equation from CFD models is used; this model is based on the finite-volume discretization of the Navier-Stokes equation. Because the mesh is unstructured with an arbitrary number of neighboring cells, the resultant matrix is sparse with a non-equal number of elements for each row. Only the preconditioned conjugate gradient (CG) or algebraic multigrid (AMG) solvers have the potential for solution stability and efficiency. However, parallelization of these solvers can be challenging. Reclamation is seeking novel, scalable parallelization of these or other innovative solvers. Of the total amount awarded, USD 300,000 will be prize money paid to freelancers. This prize challenge is envisioned to be in two stages of USD 150,000 each. The Challenge participants will have 29 weeks for Stage 1 and 34.5 weeks for Stage 2 to complete their submissions. In Stage 1, the project consists in the development and demonstration of a new linear equation sparse matrix solver (LESMS), which is parallelizable and scalable, yet still stable and efficient, while Stage 2 includes Parallelization of an existing Reclamation hydraulic- hydrologic model (SRH-2D) using the new LESMS.