Long Term Goals

• think about what the field will need "8 years from now" and what scientists want:
  • energies, derivatives of energies (most important)
  • density of states
• dirac-kohn-sham
• all-electron with ability to "understandably" switch to PAW
• ability to handle degenerate states
• use multigrid for eigensolver (O(N^2)) so we do less orthogonalization (O(N^3)). do orthogonalization on the coarse grid, and don't lose it moving to finer grids. (mid-90's codes avoided this)
• multi-GPU
• ability to scale out errors (like early GPAW). limited eventually by machine accuracy. e.g. romberg integration
• real-space
• gpu data exchange with GPU-Direct (within node and over IB ... no data exchange through MPI)
• avoid orthogonalization, use multi-grid instead
• adaptive grid (treated locally, only interacts with valence electrons)
• periodic boundary conditions
• find some small but interesting problems "along the way"

Goals for "May"

• port matlab code to GPU
• demonstrate GPU speed for simple H solid
• start looking for interesting problems, e.g.
  • how to avoid orthogonalization and handle degenerate states
  • how to extrapolate out errors
  • GPU efficiency
• real space
• periodic boundary conditions
• 1 GPU
• kohn-sham (dirac-kohn-sham too much work, but keep in mind)
• adaptive grid, all electron
• multigrid approaches, eigenvalue solver
• understand todd approach better?
• make more modular
• don't build hamiltonian like gpaw to save memory?