21 citations · 111 across the 41 of their papers we have counts for
38 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
Finding Neighbors in a Forest: A b-tree for Smoothed Particle Hydrodynamics Simulations
Aurélien Cavelan, Rubén M. Cabezón, Jonas H. M. Korndorfer +1
Finding the exact close neighbors of each fluid element in mesh-free computational hydrodynamical methods, such as the Smoothed Particle Hydrodynamics (SPH), often becomes a main b…
Algorithm-Based Fault Tolerance for Parallel Stencil Computations
Aurélien Cavelan, Florina M. Ciorba
The increase in HPC systems size and complexity, together with increasing on-chip transistor density, power limitations, and number of components, render modern HPC systems subject…
Toward a Standard Interface for User-Defined Scheduling in OpenMP
Vivek Kale, Christian Iwainsky, Michael Klemm +2
Parallel loops are an important part of OpenMP programs. Efficient scheduling of parallel loops can improve performance of the programs. The current OpenMP specification only offer…
Anomaly Detection in High Performance Computers: A Vicinity Perspective
Siavash Ghiasvand, Florina M. Ciorba
In response to the demand for higher computational power, the number of computing nodes in high performance computers (HPC) increases rapidly. Exascale HPC systems are expected to…