8 papers · 1 filter
PortLBM: A Portable Lattice Boltzmann Tool Leveraging SYCL on AMD, NVIDIA, and Intel GPUs
Alexander Strack, Marcel Graf, Alexander Van Craen +1
The lattice Boltzmann method (LBM) is a well-established approach for simulating fluid flows at the mesoscopic scale. With the stagnation of Moore's law, high-performance computing…
From Fork-Join to Asynchronous Tasks: Parallelizing Tiled Cholesky Decomposition with OpenMP and HPX
Alexander Strack, Alexander Van Craen, Dirk Pflüger
Fork-join parallelism, popularized by OpenMP, remains the dominant model for shared-memory parallel programming, but its implicit synchronization barriers can penalize algorithms w…
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…
Comparing the Performance of Heterogeneous Conjugate Gradient and Cholesky Solvers on Various Hardware Using SYCL
Tim Thüring, Alexander Strack, Dirk Pflüger
Many important real-world applications, such as System Identification with Gaussian Processes, involve solving linear systems with symmetric positive-definite matrices. The iterati…
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…
GPU-Resident Gaussian Process Regression Leveraging Asynchronous Tasks with HPX
Henrik Möllmann, Dirk Pflüger, Alexander Strack
Gaussian processes (GPs) are a widely used regression tool, but the cubic complexity of exact solvers limits their scalability. To address this challenge, we extend the GPRat libra…