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DTSTAMP:20250822T115806Z
LOCATION:Campussaal - Plenary Room
DTSTART;TZID=Europe/Stockholm:20250616T102000
DTEND;TZID=Europe/Stockholm:20250616T105000
UID:submissions.pasc-conference.org_PASC25_sess149_pos115@linklings.com
SUMMARY:P21 - Graph Abstraction for Efficient Scheduling of Asynchronous W
 orkloads on GPU
DESCRIPTION:Romin Tomasetti and Maarten Arnst (University of Liège)\n\nMan
 y computational physics simulations need to efficiently execute asynchrono
 us workloads (FEM assembly, linear algebra, etc) that can be organised as 
 a Direct Acyclic Graph (DAG). Ad hoc scheduling of these asynchronous work
 loads is an additional burden to the code and might not fully exploit the 
 available execution resources (e.g. a multi-GPU node). By contrast, archit
 ecting the code based on a graph abstraction exposes the whole computation
 al graph to the compiler/driver ahead of execution, thereby enabling as ma
 ny optimisations as possible. Therefore, a graph abstraction that can be p
 rescribed either at compile time or at runtime is necessary, and it must b
 e mappable to the best backend scheduler, thus maximising resource usage. 
 We contribute to the Kokkos implementation of this graph abstraction which
  allows for a performance portable single source code. More specifically, 
 this poster will focus on recent contributions to Kokkos::Graph that make 
 it evolve towards the C++ std::execution proposal for managing asynchronou
 s execution on generic execution resources (P2300). We will demonstrate th
 e benefits of using Kokkos::Graph both in terms of performance and softwar
 e design. We will present several examples of varying complexity, includin
 g a FEM simulation of electromagnetic wave scattering.\n\nSession Chair: C
 hris Cantwell (Imperial College London)\n\n
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