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Offsite Autotuning Approach : Performance Model Driven Autotuning Applied to Parallel Explicit ODE Methods

Title data

Seiferth, Johannes ; Korch, Matthias ; Rauber, Thomas:
Offsite Autotuning Approach : Performance Model Driven Autotuning Applied to Parallel Explicit ODE Methods.
In: Sadayappan, Ponnuswamy ; Chamberlain, Bradford L. ; Juckeland, Guido ; Ltaief, Hatem (ed.): High Performance Computing. - Cham : Springer , 2020 . - pp. 370-390 . - (Lecture Notes in Computer Science ; 12151 )
ISBN 978-3-030-50743-5
DOI: https://doi.org/10.1007/978-3-030-50743-5_19

Project information

Project title:
Project's official titleProject's id
Selbstadaption für zeitschrittbasierte Simulationstechniken auf heterogenen HPC-Systemen (SeASiTe)01IH16012A

Project financing: Bundesministerium für Bildung und Forschung

Abstract in another language

Autotuning (AT) is a promising concept to minimize the often tedious manual effort of optimizing scientific applications for a specific target platform. Ideally, an AT approach can reliably identify the most efficient implementation variant(s) for a new platform or new characteristics of the input by applying suitable program transformations and analytic models. In this work, we introduce Offsite, an offline AT approach that automates this selection process at installation time by rating implementation variants based on an analytic performance model without requiring time-consuming runtime tests. From abstract multilevel description languages, Offsite automatically derives optimized, platform-specific and problem-specific code of possible variants and applies the performance model to these variants.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: Autotuning; Performance modeling; Description language; ODE methods; ECM performance model; Shared-memory
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science II > Chair Applied Computer Science II - Univ.-Prof. Dr. Thomas Rauber
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 23 Oct 2020 06:47
Last Modified: 23 Oct 2020 06:47
URI: https://eref.uni-bayreuth.de/id/eprint/58081