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20172026
most citedAnomaly Detection in High Performance Computers: A Vicinity Perspective

11 citations · 22 across the 13 of their papers we have counts for

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cs.DC2026

JuPyLive: Seamless Migration of Jupyter Notebook Resources from Laptop to HPC

Sima Attar-Khorasani, Matthias Lieber, Siavash Ghiasvand

This work introduces JuPyLive, a migration mechanism that enables seamless transition of Jupyter notebooks between local resources of user's workstation and remote resources of hig…

cs.DC2026

BiJuTy: An Interactive HPC-Aware Big Data Cluster Lifecycle Manager and Performance Assessment Utility for JupyterHub

Apurv Deepak Kulkarni, Jan Frenzel, Siavash Ghiasvand

The increasing demand for data processing has created a pressing need for access to high-performance computing (HPC) systems. Nevertheless, leveraging these systems to execute comp…

cs.DC2025

Seamless Transitions: A Comprehensive Review of Live Migration Technologies

Sima Attar-Khorasani, Lincoln Sherpa, Matthias Lieber +1

Live migration, a technology enabling seamless transition of operational computational entities between various hosts while preserving continuous functionality and client connectiv…

cs.DC2025

SProBench: Stream Processing Benchmark for High Performance Computing Infrastructure

Apurv Deepak Kulkarni, Siavash Ghiasvand

Recent advancements in data stream processing frameworks have improved real-time data handling, however, scalability remains a significant challenge affecting throughput and latenc…

cs.DC2024

A Light-weight and Unsupervised Method for Near Real-time Behavioral Analysis using Operational Data Measurement

Tom Richard Vargis, Siavash Ghiasvand

Monitoring the status of large computing systems is essential to identify unexpected behavior and improve their performance and uptime. However, due to the large-scale and distribu…

cs.DC2019★ 11 cited

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…

cs.DC2019

Turning Privacy Constraints into Syslog Analysis Advantage

Siavash Ghiasvand, Florina M. Ciorba, Wolfgang E. Nagel

The mean time between failures (MTBF) of HPC systems is rapidly reducing, and that current failure recovery mechanisms e.g., checkpoint-restart, will no longer be able to recover t…

cs.DC2018★ 6 cited

Assessing Data Usefulness for Failure Analysis in Anonymized System Logs

Siavash Ghiasvand, Florina M. Ciorba

System logs are a valuable source of information for the analysis and understanding of systems behavior for the purpose of improving their performance. Such logs contain various ty…

cs.DC2017

Towards Adaptive Resilience in High Performance Computing

Siavash Ghiasvand, Florina M. Ciorba

Failure rates in high performance computers rapidly increase due to the growth in system size and complexity. Hence, failures became the norm rather than the exception. Different a…

cs.DC2017★ 5 cited

Anonymization of System Logs for Privacy and Storage Benefits

Siavash Ghiasvand, Florina M. Ciorba

System logs constitute valuable information for analysis and diagnosis of system behavior. The size of parallel computing systems and the number of their components steadily increa…