Job characteristics on large-scale systems: long-term analysis, quantification, and implications
HPC workload analysis and resource consumption characteristics are the key to driving
better operation practices, system procurement decisions, and designing effective resource …
better operation practices, system procurement decisions, and designing effective resource …
Systematically inferring I/O performance variability by examining repetitive job behavior
Monitoring and analyzing I/O behaviors is critical to the efficient utilization of parallel storage
systems. Unfortunately, with increasing I/O requirements and resource contention, I/O …
systems. Unfortunately, with increasing I/O requirements and resource contention, I/O …
Fine-grained scheduling for containerized hpc workloads in kubernetes clusters
Containerization technology offers lightweight OS-level virtualization, and enables
portability, reproducibility, and flexibility by packing applications with low performance …
portability, reproducibility, and flexibility by packing applications with low performance …
Autonomous task dropping mechanism to achieve robustness in heterogeneous computing systems
A Mokhtari, C Denninnart… - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
Robustness of a distributed computing system is defined as the ability to maintain its
performance in the presence of uncertain parameters. Uncertainty is a key problem in …
performance in the presence of uncertain parameters. Uncertainty is a key problem in …
A multi-gpu parallel genetic algorithm for large-scale vehicle routing problems
M Abdelatti, M Sodhi, R Sendag - 2022 IEEE High Performance …, 2022 - ieeexplore.ieee.org
The Vehicle Routing Problem (VRP) is fundamental to logistics operations. Finding optimal
solutions for VRPs related to large, real-world operations is computationally expensive …
solutions for VRPs related to large, real-world operations is computationally expensive …
Speculative scheduling for stochastic HPC applications
New emerging fields are developing a growing number of large-scale applications with
heterogeneous, dynamic and data-intensive requirements that put a high emphasis on …
heterogeneous, dynamic and data-intensive requirements that put a high emphasis on …
Convergence of high performance computing, big data, and machine learning applications on containerized infrastructures
P Liu - 2023 - upcommons.upc.edu
(English) The convergence of High Performance Computing (HPC), Big Data (BD), and
Machine Learning (ML) in the computing continuum is being pursued in earnest across the …
Machine Learning (ML) in the computing continuum is being pursued in earnest across the …
On-the-fly scheduling versus reservation-based scheduling for unpredictable workflows
Scientific insights in the coming decade will clearly depend on the effective processing of
large data sets generated by dynamic heterogeneous applications typical of workflows in …
large data sets generated by dynamic heterogeneous applications typical of workflows in …
Profiles of upcoming HPC Applications and their Impact on Reservation Strategies
With the expected convergence between HPC, BigData and AI, new applications with
different profiles are coming to HPC infrastructures. We aim at better understanding the …
different profiles are coming to HPC infrastructures. We aim at better understanding the …
[PDF][PDF] Lessons From Examining Repetitive Job Behavior and I/O Performance Variability on a Production HPC System Emily Costa Northeastern University, USA …
E Costa, T Patel, B Schwaller, J Brandt, D Tiwari - 2021 - osti.gov
As I/O demand of scientific applications increases, identifying, predicting, and analyzing I/O
behaviors is critical to ensure parallel storage systems are efficiently utilized. This paper …
behaviors is critical to ensure parallel storage systems are efficiently utilized. This paper …