GPU-Accelerated Asynchronous Error Correction for Mixed Precision Iterative Refinement

  • Hartwig Anzt (Author)
  • Piotr Luszczek (Author)
  • Jack Dongarra (Author)
  • Vincent Heuveline (Author)
    Engineering Mathematics and Computing Lab (EMCL), Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University


In hardware-aware high performance computing, block-asynchronous iteration and mixed precision iterative refinement are two techniques that may be used to leverage the computing power of SIMD accelerators like GPUs in the iterative solution of linear equation systems. although they use a very different approach for this purpose, they share the basic idea of compensating the convergence properties of an inferior numerical algorithm by a more efficient usage of the provided computing power. In this paper, we analyze the potential of combining both techniques. Therefore, we derive a mixed precision iterative refinement algorithm using a block-asynchronous iteration as an error correction solver, and compare its performance with a pure implementation of a block-asynchronous iteration and an iterative refinement method using double precision for the error correction solver. For matrices from the University of Florida Matrix collection, we report the convergence behaviour and provide the total solver runtime using different GPU architectures.




The Engineering Mathematics and Computing Lab (EMCL), directed by Prof. Dr. Vincent Heuveline, is a research group at the Interdisciplinary Center for Scientific Computing (IWR).

The EMCL Preprint Series contains publications that were accepted for the Preprint Series of the EMCL and are planned to be published in journals, books, etc. soon.

The EMCL Preprint Series was published under the roof of the Karlsruhe Institute of Technology (KIT) until April 30, 2013. As from May 01, 2013 it is published under the roof of Heidelberg University.