slackbuilds/academic/dwave-greedy

  An implementation of a steepest descent solver for binary quadratic
models.

  Steepest descent is the discrete analogue of gradient descent, but
the best move is computed using a local minimization rather rather
than computing a gradient. At each step, we determine the dimension
along which to descend based on the highest energy drop caused by a
variable flip.


  Optional building mode set with environment variables:
  - TESTS=yes (performs tests, requires dimod)