Location
Virtual
We invite you to join us for an insightful webinar hosted by the Pittsburgh Supercomputing Center:
Quantum Machine Learning Workflows: What HPC Enables and What Quantum Hardware Delivers
Date: April 3rd
Time: 1:00pm - 2:00pm (EDT)
Location: Virtual
Quantum Machine Learning (QML) is often presented as a near-term application of quantum computing, yet practical deployment remains constrained by hardware limitations and workflow complexity. In this talk, we examine how QML models are actually developed and evaluated today, with a focus on the interplay between high-performance computing (HPC) systems and emerging quantum hardware.
We walk through a real-world case study deploying a quantum convolutional neural network (QCNN) across classical simulators and multiple quantum processing units (QPUs). While simulations achieve strong performance, results on hardware show significant degradation and variability, highlighting the impact of noise, compilation strategies, and device-specific constraints.
Using this example, we outline where HPC resources play a critical role in QML, including large-scale simulation, hybrid optimization loops, and parameter exploration. We also discuss current limitations in reproducibility, benchmarking, and model portability across quantum systems.
The goal of this talk is to provide a grounded perspective on what is possible today, and to help HPC practitioners understand how systems like PSC’s Bridges-2 can support quantum workflows as the field continues to evolve.
Speaker:
Daniel Justice, Researcher, CMU
Learn more and register for this exciting event at the following link:
https://cmu.zoom.us/meeting/register/LzZ9cS6LRCi5pgQ3Cu5bNA
We look forward to seeing you there!
Best regards,
The Bridges-2 Project Team