11 citations · 22 across the 13 of their papers we have counts for
14 papers
RASER: Resilient Agent Scheduling and Execution Runtime for HPC Clusters
Sima Attar-Khorasani, Matthias Lieber, Siavash Ghiasvand
The emergence of modern agents powered by large language models has created a demand for executing long-horizon, autonomous workflows in various domains that require significant co…
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…
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…
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…
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…
asanAI: In-Browser, No-Code, Offline-First Machine Learning Toolkit
Norman Koch, Siavash Ghiasvand
Machine learning (ML) has become crucial in modern life, with growing interest from researchers and the public. Despite its potential, a significant entry barrier prevents widespre…
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…
Content-Aware Depth-Adaptive Image Restoration
Tom Richard Vargis, Siavash Ghiasvand
This work prioritizes building a modular pipeline that utilizes existing models to systematically restore images, rather than creating new restoration models from scratch. Restorat…
Assessing Anonymized System Logs Usefulness for Behavioral Analysis in RNN Models
Tom Richard Vargis, Siavash Ghiasvand
System logs are a common source of monitoring data for analyzing computing systems' behavior. Due to the complexity of modern computing systems and the large size of collected moni…
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…
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…
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…
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…
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…