arXiv subjects

Alexander Pöppl

Publications and source records attributed to Alexander Pöppl.

3 recordsLinked to original sources

arXiv2026

Node-Level Performance and Energy Characterization of Flagship Science Applications on SuperMUC-NG Phase 2

We present a systematic performance and energy-efficiency characterization of five flagship scientific workloads on SuperMUC-NG phase 2, the 28 PetaFLOPs system at the Leibniz Supercomputing Center (LRZ) equipped with Intel Xeon Platinum 8480+ and Intel Data Center GPU Max 1550 (Ponte Vecchio, PVC) accelerators. The selected codes span molecular dynamics (gromacs, lammps), astrophysics and cosmology (OpenGadget3, AthenaK), and finite-element PDE solvers from the dealii-X Center of Excellence. For each code we measure throughput and energy efficiency expressed as compute-elements per wall-clock second (or per Joule of consumed energy) on a single compute node, comparing CPU-only (SPR) against combined CPU+GPU (SPR+PVC) configurations where available. Energy measurements rely on lightweight code instrumentation with p3em, or the Energy Aware Runtime (EAR) present on the system. Our results show that GPU offload yields $4-12\times$ higher throughput and up to $15\times$ better energy efficiency compared to CPU-only execution, with lammps and AthenaK benefiting most. However, both throughput and energy gains are sensitive to problem granularity: insufficient work per GPU tile erodes the accelerator advantage, as clearly observed in AthenaK at small mesh-block sizes. The power-budget utilization is systematically lower for CPUs than it is for GPUs, indicating that even at peak useful-work rate, most applications running on CPUs leave a significant fraction of the node's thermal envelope unused.

cs.DC↗

arXiv2025

SYCL for Energy-Efficient Numerical Astrophysics: the case of DPEcho

Energy awareness and efficiency policies are gaining more attention, over pure performance (time-to-solution) Key Performance Indicators (KPIs) when comparing the possibilities offered by accelerated systems. But in a field such as numerical astrophysics, which is struggling with code refactorings for GPUs, viable porting paths have to be shown before first. After summarizing the status and recurring problems of astrophysical code accelerations, we highlight how the field would benefit from portable, vendor-agnostic GPU portings. We then employ the DPEcho SYCL benchmark to compare raw performance and energy efficiency for heterogeneous hardware on a realistic application, with the goal of helping computational astrophysicists and HPC providers make informed decisions on the most suitable hardware. Aside from GPUs showing higher efficiency, we argue on the more informative nature of energy-aware KPIs, in that they convey the specific device performance in a data-driven way. We also present a convenient, flexible and cross-platform energy-measuring pipeline. Finally, we contextualize our results through measures with different compilers, presenting device (at the cores) versus node (at the plug) energy and comparing DPEcho with the High- Performance Linpack (HPL) benchmark.

astro-ph.IM↗

arXiv2025

Solvers for Large-Scale Electronic Structure Theory: ELPA and ELSI

In this contribution, we give an overview of the ELPA library and ELSI interface, which are crucial elements for large-scale electronic structure calculations in FHI-aims. ELPA is a key solver library that provides efficient solutions for both standard and generalized eigenproblems, which are central to the Kohn-Sham formalism in density functional theory (DFT). It supports CPU and GPU architectures, with full support for NVIDIA and AMD GPUs, and ongoing development for Intel GPUs. Here we also report the results of recent optimizations, leading to significant improvements in GPU performance for the generalized eigenproblem. ELSI is an open-source software interface layer that creates a well-defined connection between "user" electronic structure codes and "solver" libraries for the Kohn-Sham problem, abstracting the step between Hamilton and overlap matrices (as input to ELSI and the respective solvers) and eigenvalues and eigenvectors or density matrix solutions (as output to be passed back to the "user" electronic structure code). In addition to ELPA, ELSI supports solvers including LAPACK and MAGMA, the PEXSI and NTPoly libraries (which bypass an explicit eigenvalue solution), and several others.

cond-mat.mtrl-sci↗