Classiq, the leading quantum computing software company, announced a demonstration of the integration between the Classiq platform and NVIDIA CUDA-Q that accelerates the workflow from high-level, AI-assisted quantum modeling through execution in hybrid quantum-classical environments, improving runtime and iteration speed for quantum research and development teams.
The updated integration reduces friction between algorithm design, rapid iteration and execution across heterogeneous compute resources, including GPUs, simulators and emerging quantum hardware. The work helps teams shorten iteration loops, a requirement for testing, benchmarking and refining hybrid approaches as high-performance computing environments evolve.
Hybrid quantum-classical computing plays a central role in how organizations evaluate and operationalize quantum-ready methods, especially as quantum workflows increasingly rely on classical acceleration for simulation, preprocessing, optimization loops and orchestration. By tightening the connection between modeling, compilation and execution, Classiq’s integration of CUDA-Q aims to help researchers and developers move faster from intent to runnable experiments and back again.
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Tests were done on a financial options-pricing benchmark using IQAE (Iterative Quantum Amplitude Estimation) available through the Classiq platform. The benchmark was implemented with the updated Classiq integration and executed via CUDA-Q. Circuit synthesis and completed execution of a 31 qubit circuit was reduced from 67 minutes to 2.5 minutes using a single NVIDIA A100 GPU.
The updated integration leverages NVIDIA AI infrastructure to achieve massive parallelization of quantum simulation execution. This enables the exploration of large and complex quantum circuits, helping to ground assumptions regarding quantum scale and quantum algorithms and paving the way for practical quantum utility at scale on emerging quantum hardware.
“Practical quantum R&D requires iteration loops that are fast, repeatable and connected to execution,” said Nir Minerbi, co-founder and CEO of Classiq. “This integration with NVIDIA CUDA-Q is designed to help teams move from high-level intent to running experiments faster, so they can test ideas, compare approaches and build toward production-ready hybrid workflows.”
“NVIDIA CUDA-Q is designed to help developers build and run hybrid quantum-classical applications across today’s accelerated computing environments and emerging quantum systems,” said Sam Stanwyck, Director of Quantum Product at NVIDIA. “Classiq’s integration of CUDA-Q allows teams to shorten iteration cycles, test ideas more quickly, and evaluate quantum-ready methods in the context of modern HPC pipelines.”
Source: GlobeNewswire