7 citations · 11 across the 3 of their papers we have counts for
6 papers · 1 filter
Closing a Source Complexity Gap between Chapel and HPX
Shreyas Atre, Chris Taylor, Patrick Diehl +1
A previous case study measured performance vs source-code complexity across multiple languages. The case study identified Chapel and HPX provide similar performance and code comple…
Asynchronous-Many-Task Systems: Challenges and Opportunities -- Scaling an AMR Astrophysics Code on Exascale machines using Kokkos and HPX
Gregor Daiß, Patrick Diehl, Jiakun Yan +9
Dynamic and adaptive mesh refinement is pivotal in high-resolution, multi-physics, multi-model simulations, necessitating precise physics resolution in localized areas across expan…
Preparing for HPC on RISC-V: Examining Vectorization and Distributed Performance of an Astrophyiscs Application with HPX and Kokkos
Patrick Diehl, Panagiotis Syskakis, Gregor Daiß +7
In recent years, interest in RISC-V computing architectures has moved from academic to mainstream, especially in the field of High Performance Computing where energy limitations ar…
Distributed, combined CPU and GPU profiling within HPX using APEX
Patrick Diehl, Gregor Daiss, Kevin Huck +6
Benchmarking and comparing performance of a scientific simulation across hardware platforms is a complex task. When the simulation in question is constructed with an asynchronous,…
Octo-Tiger's New Hydro Module and Performance Using HPX+CUDA on ORNL's Summit
Patrick Diehl, Gregor Daiß, Dominic Marcello +5
Octo-Tiger is a code for modeling three-dimensional self-gravitating astrophysical fluids. It was particularly designed for the study of dynamical mass transfer between interacting…
Memory Reduction using a Ring Abstraction over GPU RDMA for Distributed Quantum Monte Carlo Solver
Weile Wei, Eduardo D'Azevedo, Kevin Huck +3
Scientific applications that run on leadership computing facilities often face the challenge of being unable to fit leading science cases onto accelerator devices due to memory con…