Case Study: Using quantum annealing and gate-model algorithms to cut costs and accelerate time-to-insight
Challenge
A customer needed to explore a vast design space for high-performance structures with fluid dynamics constraints, but traditional CFD modeling was too computationally expensive and time-consuming to iterate through all possible permutations of design.
Solution
- Implemented quantum annealing and gate-model algorithms to explore combinatorial design spaces and identify promising candidates
- Deployed quantum filtering stage on AWS Braket to run on a variety of vendors, including IonQ and D-Wave (D-Wave no longer supported)
- Built scalable containerized HPC infrastructure using AWS ParallelCluster and EFA-enabled compute instances for CFD workloads
- Created hybrid quantum-classical workflow integrating quantum pre-filtering with traditional CFD simulation pipelines
Results
- Enabled accelerated design space exploration while maintaining computational budget constraints through quantum-enhanced workflow capabilities
- Created capability to reduce unnecessary CFD simulations through effective quantum algorithm pre-filtering of candidate structures
- Enabled evaluation of more innovative structural designs without increasing overall compute spending
- Established stepping stone framework for future quantum HPC adoption
ISC created a scalable framework for quantum-enhanced engineering workflows to reduce simulation costs while accelerating innovation for our customer.