  We use TensorNetwork [C. Roberts et al., arXiv: 1905.01330], a recently
developed API for performing tensor network contractions using accelerated
backends such as TensorFlow, to implement an optimization algorithm for the
Multi-scale Entanglement Renormalization Ansatz (MERA). We use the MERA to
approximate the ground state wave function of the infinite, one-dimensional
transverse field Ising model at criticality, and extract conformal data from
the optimized ansatz. Comparing run times of the optimization on CPUs vs. GPU,
we report a very significant speed-up, up to a factor of 200, of the
optimization algorithm when run on a GPU.
