Service interruption on Monday 11 July from 12:30 to 13:00: all the sites of the CCSD (HAL, EpiSciences, SciencesConf, AureHAL) will be inaccessible (network hardware connection).
Skip to Main content Skip to Navigation
Preprints, Working Papers, ...

Reproducibility Strategies for Parallel Preconditioned Conjugate Gradient

Abstract : The Preconditioned Conjugate Gradient method is often used in numerical simulations. While being widely used, the solver is also known for its lack of accuracy while computing the residual. In this article, we aim at a twofold goal: enhance the accuracy of the solver but also ensure its reproducibility in a message-passing implementation. We design and employ various strategies starting from the ExBLAS approach (through preserving every bit of information until final rounding) to its more lightweight performance-oriented variant (through expanding the intermediate precision). These algorithmic strategies are reinforced with programmability suggestions to assure deterministic executions. Finally, we verify these strategies on modern HPC systems: both versions deliver reproducible number of iterations, residuals, direct errors, and vector-solutions for the overhead of only 29 % (ExBLAS) and 4 % (lightweight) on 768 processes.
Complete list of metadata

Cited literature [35 references]  Display  Hide  Download
Contributor : Roman Iakymchuk Connect in order to contact the contributor
Submitted on : Friday, May 15, 2020 - 1:10:10 PM
Last modification on : Sunday, June 26, 2022 - 2:49:44 AM


Files produced by the author(s)


  • HAL Id : hal-02391618, version 2


Roman Iakymchuk, Maria Barreda, Matthias Wiesenberger, José I Aliaga, Enrique S Quintana-Ortí. Reproducibility Strategies for Parallel Preconditioned Conjugate Gradient. 2020. ⟨hal-02391618v2⟩



Record views


Files downloads