|
|
|||||||||||||||||
 |
Minimizing Power Waste in Heterogenous Computing via Adaptive Uncore Scaling
Michael E. Papka, Seyfal Sultanov, Zhiling Lan November 16, 2025 - November 21, 2025 High-performance computing (HPC) systems are essential for scientific discovery and engineering innovation. However, their growing power demands pose… Read more |
 |
OAC Core: AIMCI: Artificial Intelligence for Managing Cyberinfrastructure
Michael E. Papka, Zhiling Lan July 27, 2025 - July 29, 2025 Advanced cyberinfrastructure (CI) is undergoing disruptive changes in system architectures and application workloads. The landscape of… Read more |
 |
Parameterized Algorithms for Non-uniform All-to-all
Ke Fan, Sidharth Kumar July 20, 2025 - July 23, 2025 MPI_Alltoallv generalizes the uniform all-to-all communication (MPI_Alltoall) by enabling the exchange of data-blocks of varied sizes among… Read more |
 |
CQSim+: Symbiotic Simulation for Multi-Resource Scheduling in High-Performance Computing
Michael E. Papka, Shambhawi Sharma, Xi Wang, Yash Kurkure, Zhiling Lan June 23, 2025 - June 26, 2025 Efficient job scheduling is crucial in high-performance computing (HPC), balancing user demands for quick job turnaround with facility goals for high… Read more |
 |
MFNetSim: A Multi-Fidelity Network Simulation Framework for Multi-Trafic Modeling of Dragonfly Systems
Xi Wang, Zhiling Lan June 23, 2025 In high-performance computing (HPC), modern supercomputers typically provide exclusive computing resources to user applications. Nevertheless, the… Read more |
 |
Multi-Node Multi-GPU Datalog
Ahmedur Rahman Shovon, Sidharth Kumar June 8, 2025 - June 11, 2025 Datalog, a declarative logic programming language that operates bottom-up, has experienced increasing popularity due to its natural handling of… Read more |
 |
Preventing Workload Interference with Intelligent Routing and Flexible Job Placement Strategy on Dragonfly system (poster)
Xi Wang, Zhiling Lan May 8, 2025 Motivation: - Dragonfly networks suffer from inter-job interference due to shared global links. - Existing routing algorithms fail to account for… Read more |
 |
MAGUS: Memory-Throughput-Based Uncore Frequency Scaling on Heterogeneous Systems (poster)
Michael E. Papka, Seyfal Sultanov, Zhiling Lan May 8, 2025 Prior uncore frequency tuning studies have primarily focused on conventional HPC workloads running on CPU-only systems. As HPC advances toward… Read more |
 |
MNMGDatalog: A Scalable Multi-Node Multi-GPU Datalog Engine (poster)
Ahmedur Rahman Shovon, Sidharth Kumar May 8, 2025 Research Contributions: - First ever Datalog engine designed for multinode multi-GPU HPC systems, outperforming state-of-the-art shared-memory… Read more |
 |
Evaluating SZ3 Compressor Performance on High Energy Physics Data (poster)
Amy Byrnes May 8, 2025 Motivation: - The Large Hadron Collider (LHC) has created hundreds of petabytes of data. The High-Luminosity LHC (HL-LHC) will produce orders of… Read more |
 |
Energy Efficiency of LLM Inference Across Various AI Accelerators (poster)
Zhiling Lan May 8, 2025 In recent years, numerous hardware accelerators have been developed to meet the rising demand for machine learning (ML) workloads, and Large Language… Read more |
 |
LASSI-EE: Leveraging LLMs to Automate Energy-Aware Refactoring of Parallel Scientific Codes (poster)
Matthew Dearing, Yiheng Tao, Zhiling Lan May 8, 2025 While large language models (LLMs) are increasingly used for generating parallel scientific code, most current efforts emphasize functional… Read more |
 |
On-Demand Pilot Job Scheduling for Adaptive Execution of HEP Workflows on HPC Systems (poster)
Michael E. Papka, Shambhawi Sharma, Xi Wang, Zhiling Lan May 8, 2025 HEP workflows often consist of complex DAGs with streaming job arrivals that challenge traditional static scheduling approaches. We introduce a… Read more |
 |
Temporal Causal Graph Discovery in Complex HPC Network Traffic Simulations (poster)
Matthew Dearing, Zhiling Lan May 8, 2025 Motivation: • Parallel Discrete Event Simulations (PDES) offers accurate HPC simulations but is computationally intensive and slow to scale. •… Read more |
 |
Overcoming RL Limitations in HPC Scheduling: A Model-Based MCTS Approach for Practical Deployment (poster)
Michael E. Papka, Yash Kurkure, Zhiling Lan May 8, 2025 High-performance computing (HPC) job scheduling has seen promising advances with Deep Reinforcement Learning (DRL). However, challenges such as low… Read more |
 |
From Prompts to Priorities: Pairwise Learning-to-Rank Scheduling for Low-Latency LLM Serving (poster)
Matthew Dearing, Xi Wang, Yiheng Tao, Zhiling Lan May 8, 2025 Large language model (LLM) requests vary widely: a short factual query may produce only a few dozen tokens, while multi-step reasoning or proof… Read more |
 |
EMMA: Efficient Multi-node Memory-aware AllReduce Algorithms (poster)
Ke Fan, Sidharth Kumar May 8, 2025 AllReduce is a critical collective in both HPC and large-scale AI workloads. However, scaling it to Exascale systems presents key challenges due to… Read more |
 |
Performance Characterization and Tuning of Non-uniform All-to-all Data Exchanges (poster)
Ke Fan, Sidharth Kumar May 8, 2025 Non-uniform MPI_Alltoallv communication is critical in many high-performance computing (HPC) applications where data exchange patterns vary… Read more |
 |
Scaling Computational Fluid Dynamics: In Situ Visualization of NekRS using SENSEI
Michael E. Papka November 12, 2023 - November 17, 2023 In the realm of Computational Fluid Dynamics (CFD), the demand for memory and computation resources is extreme, necessitating the use of… Read more |
 |
ChemoGraph: Interactive Visual Exploration of the Chemical Space
Michael E. Papka June 12, 2023 - June 16, 2023 Honorable Mention in the EuroVis Best Paper Category Exploratory analysis of the chemical space is an important task in the field of cheminformatics… Read more |
 |
The State of the Art in Visualizing Dynamic Multivariate Networks
Michael E. Papka June 12, 2023 - June 16, 2023 Most real-world networks are both dynamic and multivariate in nature, meaning that the network is associated with various attributes and both the… Read more |
 |
Visual Analysis and Detection of Contrails in Aircraft Engine Simulations
Carla Floricel, G. Elisabeta Marai, Md Nafiul Alam Nipu January 1, 2023 Contrails are condensation trails generated from emitted particles by aircraft engines, which perturb Earth’s radiation budget. Simulation modeling… Read more |
 |
DRAS: Deep Reinforcement Learning for Cluster Scheduling in High Performance Computing
Michael E. Papka December 1, 2022 Cluster schedulers are crucial in high-performance computing (HPC). They determine when and which user jobs should be allocated to available system… Read more |
 |
Visual Analysis and Detection of Contrails in Aircraft Engine Simulations
Carla Floricel, G. Elisabeta Marai, Md Nafiul Alam Nipu October 16, 2022 - October 21, 2022 Contrails are condensation trails generated from emitted particles by aircraft engines, which perturb Earth’s radiation budget. Simulation… Read more |
 |
Linking scientific instruments and computation: Patterns, technologies, and experiences
Michael E. Papka October 14, 2022 Powerful detectors at modern experimental facilities routinely collect data at multiple GB/s. Online analysis methods are needed to enable the… Read more |
 |
Moving from Composable to Programmable
Andrew Johnson, Lance Long, Luc Renambot, Maxine Brown, Zhongyi Chen June 3, 2022 In today’s Big Data era, data scientists require modern workflows to quickly analyze large-scale datasets using complex codes to maintain the… Read more |
 |
Composable Infrastructures for an Academic Research Environment: Lessons Learned
Andrew Johnson, Lance Long, Luc Renambot, Maxine Brown, Zhongyi Chen June 3, 2022 Composable infrastructure holds the promise of accelerating the pace of academic research and discovery by enabling researchers to tailor the… Read more |
 |
Monitoring COMPaaS
April 29, 2022 The Electronic Visualization Laboratory at the University of Illinois Chicago acquired a 24 compute node, 64 GPU composable infrastructure compute… Read more |
 |
Moving from Composable to Programmable
Andrew Johnson, Lance Long, Luc Renambot, Maxine Brown, Zhongyi Chen April 15, 2022 In today’s Big Data era, data scientists require modern workflows to quickly analyze large-scale datasets using complex codes to maintain the… Read more |
 |
Composable Infrastructures for an Academic Research Environment: Lessons Learned
Andrew Johnson, Lance Long, Luc Renambot, Maxine Brown, Timothy Bargo April 15, 2022 Composable infrastructure holds the promise of accelerating the pace of academic research and discovery by enabling researchers to tailor the… Read more |
 |
A Distributed Graph Approach for Pre-processing Linked RDF Data Using Supercomputers
Andrew Johnson, Michael Lewis May 18, 2017 Efficient RDF, graph-based queries are becoming more pertinent based on the increased interest in data analytics and its intersection with large… Read more |
 |
Improving Sparse Data Movement Performance Using Multiple Paths on the Blue Gene/Q Supercomputer
Andrew Johnson, Huy A. Bui January 1, 2016 In situ analysis has been proposed as a promising solution to glean faster insights and reduce the amount of data to storage. A critical challenge… Read more |
 |
Improving Communication Throughput by Multipath Load Balancing on Blue Gene/Q
Andrew Johnson, Huy A. Bui December 16, 2015 - December 19, 2015 Achievable networking performance of applications in a supercomputer depends on the exact combination of the communication patterns of the… Read more |
 |
Multipath Load Balancing for M x N Communication Patterns on the Blue Gene⁄Q Supercomputer Interconnection Network
Andrew Johnson, Huy A. Bui September 8, 2015 - September 11, 2015 Achievable networking performance of applications in a supercomputer depends on the exact combination of the communication patterns of the… Read more |
 |
Two-phase IO Enabling Large-scale Performance Introspection (poster)
Ke Fan, Sidharth Kumar November 12, 1970 - November 17, 1970 Numerous sophisticated profiling and visualization tools have been developed to enable programmers to expose semantic information from their… Read more |
