We analyze minimization algorithms for L\-convex functions in discrete convex analysis, and establish exact bounds for the number of iterations required by the steepest descent algorithm and its variants.
Nuno CardosoPaulo J. SilvaOrlando OliveiraPedro Bicudo
In this work, we consider the GPU implementation of the steepest descent method with Fourier acceleration for Laudau gauge fixing, using CUDA. The performance of the code in a Tesla C2070 GPU is compared with a parallel CPU implementation.
We prove that the Steepest Descent algorithm applied to the minimization of total stored energies with rank-one related rotationally symmetric energy wells does not produce relaxing vectorial microstructures with non-trivial Young measures.
We construct a. family of symmet ric weight connect ion networks that take expon ential time to reach a stable configuration when th e sequential steepest descent update rule is used .
