@article{20,
  abstract     = {{Approximate computing has shown to provide new ways to improve performance
and power consumption of error-resilient applications. While many of these
applications can be found in image processing, data classification or machine
learning, we demonstrate its suitability to a problem from scientific
computing. Utilizing the self-correcting behavior of iterative algorithms, we
show that approximate computing can be applied to the calculation of inverse
matrix p-th roots which are required in many applications in scientific
computing. Results show great opportunities to reduce the computational effort
and bandwidth required for the execution of the discussed algorithm, especially
when targeting special accelerator hardware.}},
  author       = {{Lass, Michael and Kühne, Thomas and Plessl, Christian}},
  issn         = {{1943-0671}},
  journal      = {{Embedded Systems Letters}},
  number       = {{2}},
  pages        = {{ 33--36}},
  publisher    = {{IEEE}},
  title        = {{{Using Approximate Computing for the Calculation of Inverse Matrix p-th Roots}}},
  doi          = {{10.1109/LES.2017.2760923}},
  volume       = {{10}},
  year         = {{2018}},
}