6 papers
Is RISC-V Ready for Machine Learning? Portable Gaussian Processes Using Asynchronous Tasks
Alexander Strack, Patrick Diehl, Dirk Pflüger
Gaussian processes are widely used in machine learning domains but remain computationally demanding, limiting their efficient scalability across emerging hardware platforms. The GP…
Radiation Hydrodynamics at Scale: Comparing MPI and Asynchronous Many-Task Runtimes with FleCSI
Alexander Strack, Hartmut Kaiser, Dirk Pflüger
Writing efficient distributed code remains a labor-intensive and complex endeavor. To simplify application development, the Flexible Computational Science Infrastructure (FleCSI) f…
Asynchronous-Many-Task Systems: Challenges and Opportunities -- Scaling an AMR Astrophysics Code on Exascale machines using Kokkos and HPX
Gregor DaiÃ, 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…
Parallel FFTW on RISC-V: A Comparative Study including OpenMP, MPI, and HPX
Alexander Strack, Christopher Taylor, Dirk Pflüger
Rapid advancements in RISC-V hardware development shift the focus from low-level optimizations to higher-level parallelization. Recent RISC-V processors, such as the SOPHON SG2042,…
GPRat: Gaussian Process Regression with Asynchronous Tasks
Maksim Helmann, Alexander Strack, Dirk Pflüger
Python is the de-facto language for software development in artificial intelligence (AI). Commonly used libraries, such as PyTorch and TensorFlow, rely on parallelization built int…
A HPX Communication Benchmark: Distributed FFT using Collectives
Alexander Strack, Dirk Pflüger
Due to increasing core counts in modern processors, several task-based runtimes emerged, including the C++ Standard Library for Concurrency and Parallelism (HPX). Although the asyn…