2 citations · 2 across the 11 of their papers we have counts for
12 papers
Report of the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science
Lois Curfman McInnes, Dorian Arnold, Prasanna Balaprakash +45
Scientific computing is undergoing rapid transformation as advances in artificial intelligence, heterogeneous computing, automation, and data-intensive research reshape not only co…
COMPASS: A Unified Decision-Intelligence System for Navigating Performance Trade-off in HPC
Ankur Lahiry, Banooqa Banday, Yugesh Bhattarai +2
HPC systems expose many configuration parameters that jointly drive competing objectives. Existing tools such as autotuners recommend good configurations but do not identify minima…
Optimas: An Intelligent Analytics-Informed Generative AI Framework for Performance Optimization
Mohammad Zaeed, Tanzima Z. Islam, Vladimir Indic
Large language models (LLMs) show promise for automated code optimization. However, without performance context, they struggle to produce correct and effective code transformations…
Attention-Informed Surrogates for Navigating Power-Performance Trade-offs in HPC
Ashna Nawar Ahmed, Banooqa Banday, Terry Jones +1
High-Performance Computing (HPC) schedulers must balance user performance with facility-wide resource constraints. The task boils down to selecting the optimal number of nodes for…
A Distributed Framework for Causal Modeling of Performance Variability in GPU Traces
Ankur Lahiry, Ayush Pokharel, Banooqa Banday +5
Large-scale GPU traces play a critical role in identifying performance bottlenecks within heterogeneous High-Performance Computing (HPC) architectures. However, the sheer volume an…
Report of the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science
Lois Curfman McInnes, Dorian Arnold, Prasanna Balaprakash +40
This report summarizes insights from the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Sc…
Opal: A Modular Framework for Optimizing Performance using Analytics and LLMs
Mohammad Zaeed, Tanzima Z. Islam, Vladimir Inđić
Large Language Models (LLMs) show promise for automated code optimization but struggle without performance context. This work introduces Opal, a modular framework that connects per…
HPC Digital Twins for Evaluating Scheduling Policies, Incentive Structures and their Impact on Power and Cooling
Matthias Maiterth, Wesley H. Brewer, Jaya S. Kuruvella +8
Schedulers are critical for optimal resource utilization in high-performance computing. Traditional methods to evaluate schedulers are limited to post-deployment analysis, or simul…
Scalable GPU Performance Variability Analysis framework
Ankur Lahiry, Ayush Pokharel, Seth Ockerman +3
Analyzing large-scale performance logs from GPU profilers often requires terabytes of memory and hours of runtime, even for basic summaries. These constraints prevent timely insigh…
WANDER: An Explainable Decision-Support Framework for HPC
Ankur Lahiry, Banooqa Banday, Yugesh Bhattarai +1
High-performance computing (HPC) systems expose many interdependent configuration knobs that impact runtime, resource usage, power, and variability. Existing predictive tools model…
Data-Driven Analysis to Understand GPU Hardware Resource Usage of Optimizations
Tanzima Z. Islam, Aniruddha Marathe, Holland Schutte +1
With heterogeneous systems, the number of GPUs per chip increases to provide computational capabilities for solving science at a nanoscopic scale. However, low utilization for sing…
Novel Representation Learning Technique using Graphs for Performance Analytics
Tarek Ramadan, Ankur Lahiry, Tanzima Z. Islam
The performance analytics domain in High Performance Computing (HPC) uses tabular data to solve regression problems, such as predicting the execution time. Existing Machine Learnin…