activity
20172025
most citedA Smoothed Particle Hydrodynamics Mini-App for Exascale

21 citations · 111 across the 41 of their papers we have counts for

collaborators

45 papers

cs.DC2025

SIREN: Software Identification and Recognition in HPC Systems

Thomas Jakobsche, Fredrik Robertsén, Jessica R. Jones +2

HPC systems use monitoring and operational data analytics to ensure efficiency, performance, and orderly operations. Application-specific insights are crucial for analyzing the inc…

cs.DC2025

AEGIS: Runtime-Guided GPU Collocation for Multi-Tenant Deep Learning Training

Ehsan Yousefzadeh-Asl-Miandoab, Florina M. Ciorba, Büşra Karatay Demiray +2

Deep learning training commonly runs on shared multi-tenant GPU servers, where exclusive allocation provides isolation but can leave resources underutilized and increase queueing t…

cs.DC2025

A Comparative Study of OpenMP Scheduling Algorithm Selection Strategies

Jonas H. Müller Korndörfer, Ali Mohammed, Ahmed Eleliemy +3

Scientific and data science applications are becoming increasingly complex, with growing computational and memory demands. Modern high performance computing (HPC) systems provide h…

cs.DC2025

Scalable Genomic Context Analysis with GCsnap2 on HPC Clusters

Reto Krummenacher, Osman Seckin Simsek, Michèle Leemann +4

GCsnap2 Cluster is a scalable, high performance tool for genomic context analysis, developed to overcome the limitations of its predecessor, GCsnap1 Desktop. Leveraging distributed…

cs.DC2025

An Autonomy Loop for Dynamic HPC Job Time Limit Adjustment

Thomas Jakobsche, Osman Seckin Simsek, Jim Brandt +2

High Performance Computing (HPC) systems rely on fixed user-provided estimates of job time limits. These estimates are often inaccurate, resulting in inefficient resource use and t…

astro-ph.IM2025

From particles to precision. Simulating subsonic turbulence with Smoothed Particle Hydrodynamics

Rubén M. Cabezón, Domingo García-Senz, Oliver Avril +6

The numerical simulation of subsonic turbulence with smoothed particle hydrodynamics (SPH) has traditionally been hampered by zeroth-order (E0) errors, inaccurate gradient evaluati…

cs.CR2024

Using Malware Detection Techniques for HPC Application Classification

Thomas Jakobsche, Florina M. Ciorba

HPC systems face security and compliance challenges, particularly in preventing waste and misuse of computational resources by unauthorized or malicious software that deviates from…

cs.DC2024

Autonomy Loops for Monitoring, Operational Data Analytics, Feedback, and Response in HPC Operations

Francieli Boito, Jim Brandt, Valeria Cardellini +24

Many High Performance Computing (HPC) facilities have developed and deployed frameworks in support of continuous monitoring and operational data analytics (MODA) to help improve ef…

cs.DC2023★ 9 cited

Accurate Measurement of Application-level Energy Consumption for Energy-Aware Large-Scale Simulations

Osman Seckin Simsek, Jean-Guillaume Piccinali, Florina M. Ciorba

Sustainability in high performance computing (HPC) is a major challenge not only for HPC centers and their users, but also for society as the climate goals become stricter. A lot o…

cs.DC2023

DaphneSched: A Scheduler for Integrated Data Analysis Pipelines

Ahmed Eleliemy, Florina M. Ciorba

DAPHNE is a new open-source software infrastructure designed to address the increasing demands of integrated data analysis (IDA) pipelines, comprising data management (DM), high pe…

astro-ph.IM2023★ 10 cited

Cornerstone: Octree Construction Algorithms for Scalable Particle Simulations

Sebastian Keller, Aurélien Cavelan, Rubén Cabezon +2

This paper presents an octree construction method, called Cornerstone, that facilitates global domain decomposition and interactions between particles in mesh-free numerical simula…

cs.DC2022

Challenges and Opportunities of Machine Learning for Monitoring and Operational Data Analytics in Quantitative Codesign of Supercomputers

Thomas Jakobsche, Nicolas Lachiche, Florina M. Ciorba

This work examines the challenges and opportunities of Machine Learning (ML) for Monitoring and Operational Data Analytics (MODA) in the context of Quantitative Codesign of Superco…

cs.DC2022★ 8 cited

Application Experiences on a GPU-Accelerated Arm-based HPC Testbed

Wael Elwasif, William Godoy, Nick Hagerty +28

This paper assesses and reports the experience of ten teams working to port,validate, and benchmark several High Performance Computing applications on a novel GPU-accelerated Arm t…

cs.DC2022★ 3 cited

First Experiences in Performance Benchmarking with the New SPEChpc 2021 Suites

Holger Brunst, Sunita Chandrasekaran, Florina Ciorba +7

Modern HPC systems are built with innovative system architectures and novel programming models to further push the speed limit of computing. The increased complexity poses challeng…

cs.DC2021

An Execution Fingerprint Dictionary for HPC Application Recognition

Thomas Jakobsche, Nicolas Lachiche, Aurélien Cavelan +1

Applications running on HPC systems waste time and energy if they: (a) use resources inefficiently, (b) deviate from allocation purpose (e.g. cryptocurrency mining), or (c) encount…

cs.DC2021★ 15 cited

LB4OMP: A Dynamic Load Balancing Library for Multithreaded Applications

Jonas H. Müller Korndörfer, Ahmed Eleliemy, Ali Mohammed +1

Exascale computing systems will exhibit high degrees of hierarchical parallelism, with thousands of computing nodes and hundreds of cores per node. Efficiently exploiting hierarchi…

cs.DC2021

A Resourceful Coordination Approach for Multilevel Scheduling

Ahmed Eleliemy, Florina M. Ciorba

HPC users aim to improve their execution times without particular regard for increasing system utilization. On the contrary, HPC operators favor increasing the number of executed a…

cs.DC2021

A Distributed Chunk Calculation Approach for Self-scheduling of Parallel Applications on Distributed-memory Systems

Ahmed Eleliemy, Florina M. Ciorba

Loop scheduling techniques aim to achieve load-balanced executions of scientific applications. Dynamic loop self-scheduling (DLS) libraries for distributed-memory systems are typic…

cs.DC2020

Resiliency in Numerical Algorithm Design for Extreme Scale Simulations

Emmanuel Agullo, Mirco Altenbernd, Hartwig Anzt +33

This work is based on the seminar titled ``Resiliency in Numerical Algorithm Design for Extreme Scale Simulations'' held March 1-6, 2020 at Schloss Dagstuhl, that was attended by a…

cs.CE2020★ 21 cited

A Smoothed Particle Hydrodynamics Mini-App for Exascale

Aurélien Cavelan, Rubén M. Cabezón, Michal Grabarczyk +1

The Smoothed Particles Hydrodynamics (SPH) is a particle-based, meshfree, Lagrangian method used to simulate multidimensional fluids with arbitrary geometries, most commonly employ…

cs.DC2020

Mapping Matters: Application Process Mapping on 3-D Processor Topologies

Jonas H. Müller Korndörfer, Mario Bielert, Laércio L. Pilla +1

Applications' performance is influenced by the mapping of processes to computing nodes, the frequency and volume of exchanges among processing elements, the network capacity, and t…

cs.DC2019

SimAS: A Simulation-assisted Approach for the Scheduling Algorithm Selection under Perturbations

Ali Mohammed, Florina M. Ciorba

Many scientific applications consist of large and computationally-intensive loops. Dynamic loop self-scheduling (DLS) techniques are used to parallelize and to balance the load dur…

cs.DC2019

Two-level Dynamic Load Balancing for High Performance Scientific Applications

Ali Mohammed, Aurelien Cavelan, Florina M. Ciorba +2

Scientific applications are often complex, irregular, and computationally-intensive. To accommodate the ever-increasing computational demands of scientific applications, high-perfo…

cs.DC2019

An Approach for Realistically Simulating the Performance of Scientific Applications on High Performance Computing Systems

Ali Mohammed, Ahmed Eleliemy, Florina M. Ciorba +2

Scientific applications often contain large, computationally-intensive, and irregular parallel loops or tasks that exhibit stochastic characteristics. Applications may suffer from…