32 citations · 59 across the 27 of their papers we have counts for
14 papers · 1 filter
CALIPER: Calibrating HPC/AI Network Simulators
Seyyidahmed Lahmer, Daniel Seibel, Srijeet Basu +9
Network simulation plays an important role in HPC/AI system research by enabling exploration of network architectures, communication strategies, and system configurations at scales…
4D Parallelism Unlocks Exascale Bayesian Neural Networks for High-Fidelity Atmospheric Modeling
Deifilia Kieckhefen, Juan Pedro Gutiérrez Hermosillo Muriedas, Lars Helge Heyen +12
We present BEAST, the first-ever Bayesian Swin Transformer for atmospheric forecasting on 0.25 global resolution able to accurately quantify both aleatoric and epistemic un…
Characterizing the Scalability and Performance of Large-Scale AI Training Under Multi-Tenancy
Jacopo Raffi, Thomas Pasquali, Lorenzo Piarulli +6
Characterising AI workload performance on modern HPC systems requires understanding both their scalability in isolation and their behaviour under concurrent execution. However, the…
Novel Iterative Construction Methods for the Blocking Job Shop Scheduling Problem
Adel Dabah, Karima Rihane, Hocine Saadi +4
The Blocking Job-Shop Scheduling Problem (BJSSP) arises in modern and complex manufacturing, production, logistics, and service where no intermediate storage is allowed between con…
A GPU-Accelerated Blocked Adaptive Randomized Range Finder Based on an Implicit Householder QR Decomposition
Carolin Penke, Andreas Herten
Low-rank methods can reduce the memory and computational requirements of deep neural network training in approaches such as GaLore. Randomized range finders offer an attractive alt…
Performance Evaluation of Fast Fourier Transforms on Emerging RISC-V Hardware with Vector Extension Support
Daniel Seibel, Kaveh Haghighi Mood, Jayesh Badwaik +3
This manuscript presents a performance evaluation of Fast Fourier Transform (FFT) implementations on emerging processors supporting the RISC-V Vector Extension (RVV 1.0). By introd…
Fourier Neural Operators for Rayleigh-Bénard Convection
Chelsea Maria John, Thibaut Lunet, Sebastian Götschel +3
We propose an improved Fourier Neural Operator (FNO) for modeling two-dimensional Rayleigh-Bénard convection by predicting time increments instead of full solutions, achieving high…
Coupling Complementary Simulations for Combined Performance and Energy Optimization
Adel Dabah, Gregor Häfner, Sonja Happ +3
Polymer simulations are among the most computationally demanding workloads in soft-matter research, often requiring days of execution and high energy consumption to achieve physica…
Nucleon strange electromagnetic form factors using twisted-mass fermions at the physical point
Constantia Alexandrou, Simone Bacchio, Mathis Bode +7
We present the strange electromagnetic form factors of the nucleon using lattice QCD with twisted mass clover-improved fermions and quark masses tuned to their physical…
Efficient Accelerated Graph Edit Distance Computation on GPU
Adel Dabah, Andreas Herten
Graph representation is a powerful abstraction of real-world objects and relations. Computing the Graph Edit Distance (GED) between graphs is critical in domains such as bioinforma…
Strangeness of nucleons from lattice QCD
Constantia Alexandrou, Simone Bacchio, Mathis Bode +7
We present the strange electromagnetic form factors of the nucleon using lattice QCD simulations with degenerate light, a strange, and a charm quark in the sea with masses tuned to…
Nucleon strange electromagnetic form factors from lattice QCD
Constantia Alexandrou, Simone Bacchio, Mathis Bode +7
We present the nucleon strange electromagnetic form factors using four lattice QCD ensembles with twisted mass clover-improved fermions and quark masses tuned to approx…
exaCB: Reproducible Continuous Benchmark Collections at Scale Leveraging an Incremental Approach
Jayesh Badwaik, Mathis Bode, Michal Rajski +1
The increasing heterogeneity of high-performance computing (HPC) systems and the transition to exascale architectures require systematic and reproducible performance evaluation acr…
High-performance Vector-length Agnostic Quantum Circuit Simulations on ARM Processors
Ruimin Shi, Gabin Schieffer, Pei-Hung Lin +3
ARM SVE and RISC-V RVV are emerging vector architectures in high-end processors that support vectorization of flexible vector length. In this work, we leverage an important workloa…