5 papers
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…
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…
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…
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…