Wavelet-Based Density Functional Theory on Massively Parallel Hybrid Architectures

Abstract : In this chapter, we describe the GPU acceleration of density functional theory (DFT) calculations based on wavelet basis sets as realized in the BigDFT code. Daubechies wavelets have not been traditionally used for DFT calculations, but they exhibit properties that make them attractive for both accurate and efficient DFT simulations. Here we explain how an existing MPI parallel wavelet-based DFT implementation can benefit from the computational power of GPUs by offloading numerically intensive operations to GPUs.
Complete list of metadatas

https://hal.archives-ouvertes.fr/hal-01239245
Contributor : Jean-Francois Méhaut <>
Submitted on : Monday, December 7, 2015 - 3:30:18 PM
Last modification on : Thursday, April 4, 2019 - 5:08:04 PM

Identifiers

  • HAL Id : hal-01239245, version 1

Citation

Luigi Genovese, Brice Videau, Damien Caliste, Jean-François Méhaut, Stefan Goedecker, et al.. Wavelet-Based Density Functional Theory on Massively Parallel Hybrid Architectures. Ross Walker. Electronic Structure Calculations on Graphics Processing Units: From Quantum Chemistry to Condensed Matter Physics, Wiley-Blackwell, 2016, 1118661788. ⟨hal-01239245⟩

Share

Metrics

Record views

374