Sehr geehrte Damen und Herren,
Die untenstehende Veranstaltung findet nicht statt.
Eine neue Ankuendigung wird erfolgen, sobald ein neuer Termin feststeht.
Mit freundlichen Gruessen,
Markus Hoehnerbach
On 06-Mar-20 20:56, Markus Hoehnerbach wrote:
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* Einladung
* Informatik-Oberseminar
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Zeit: Montag, 23. Maerz 2020, 10.00 Uhr Ort: Raum 115, Rogowski-Gebaeude,
Referent: Markus Hoehnerbach M.Sc. High-Performance and Automatic Computing
Thema: A Framework for the Vectorization of Molecular Dynamics Kernels
Abstract:
We introduce a domain-specific language (DSL) for many-body potentials, which are used in molecular dynamics (MD) simulations in the area of materials science. We also introduce a compiler to translate the DSL into high-performance code suitable for modern supercomputers.
We begin by studying ways to speedup up potentials on supercomputers using two case studies: The Tersoff and the AIREBO potentials. In both case studies, we identify a number of optimizations, both domain-specific and general, to achieve speedups of up to 5x; we also introduce a method to keep the resulting code performance portable.
During the AIREBO case study, we also discover that the existing code contains a number of errors. This experience motivates us to include the derivation step, the most error-prone step in manual optimization, in our automation effort.
After having identified beneficial optimization techniques, we create a ``potential compiler'', short PotC, which generates fully-usable performance-portable potential implementations from specifications written in our DSL. DSL code is significantly shorter (20x to 30x) than a manual code, reducing both manual work and opportunities to introduce bugs.
We present performance results on five different platforms: Three CPU platforms (Broadwell, Knights Landing, and Skylake) and two GPU platforms (Pascal and Volta). While the performance in some cases remains far below that of hand-written code, it also manages to match or exceed manually written implementations in other cases. For these cases, we achieve speedups of up to 9x compared to non-vectorized code.
Es laden ein: die Dozentinnen und Dozenten der Informatik