Optimizing Excited-State Electronic-Structure Codes for Intel Knights Landing: A Case Study on the BerkeleyGW Software

Derek Vigil-Fowler, Jack Deslippe, Felipe da Jornada, Taylor Barnes, Nathan Wichmann, Karthik Raman, Ruchira Sasanka, Steven Louie

Research output: Contribution to conferencePaperpeer-review

2 Scopus Citations

Abstract

We profile and optimize calculations performed with the BerkeleyGW [2,3] code on the Xeon-Phi architecture. BerkeleyGW depends both on hand-tuned critical kernels as well as on BLAS and FFT libraries. We describe the optimization process and performance improvements achieved. We discuss a layered parallelization strategy to take advantage of vector, thread and node-level parallelism. We discuss locality changes (including the consequence of the lack of L3 cache) and effective use of the on-package high-bandwidth memory. We show preliminary results on Knights-Landing including a roofline study of code performance before and after a number of optimizations. We find that the GW method is particularly well-suited for many-core architectures due to the ability to exploit a large amount of parallelism over plane-wave components, band-pairs, and frequencies.

Conference

ConferenceInternational Workshops on High Performance Computing, ISC High Performance 2016 and Workshop on 2nd International Workshop on Communication Architectures at Extreme Scale, ExaComm 2016, Workshop on Exascale Multi/Many Core Computing Systems, E-MuCoCoS 2016, HPC I/O in the Data Center, HPC-IODC 2016, Application Performance on Intel Xeon Phi – Being Prepared for KNL and Beyond, IXPUG 2016, International Workshop on OpenPOWER for HPC, IWOPH 2016, International Workshop on Performance Portable Programming Models for Accelerators, P^3MA 2016, Workshop on Virtualization in High-Performance Cloud Computing, VHPC 2016, Workshop on Performance and Scalability of Storage Systems, WOPSSS 2016
Country/TerritoryGermany
CityFrankfurt
Period19/06/1623/06/16

Bibliographical note

Publisher Copyright:
© Springer International Publishing AG 2016.

NREL Publication Number

  • NREL/CP-5K00-67446

Keywords

  • BerkeleyGW
  • optimization
  • performance

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