Classiq has integrated its quantum software platform with the NVIDIA CUDA-Q framework to facilitate high-level modeling and hybrid execution in heterogeneous compute environments. This updated workflow connects AI-assisted functional modeling with classical acceleration for tasks such as circuit synthesis, simulation, and optimization loops. The integration is designed for High-Performance Computing (HPC) environments where quantum workloads utilize classical infrastructure for pre-processing and orchestration. Users access this functionality through a terminal command within the Classiq development studio to automate the transition from functional intent to hardware-ready quantum circuits.
Performance testing was conducted using an Iterative Quantum Amplitude Estimation (IQAE) benchmark focused on financial options pricing. On a 31-qubit circuit executed via a single NVIDIA A100 GPU, the integration reduced the end-to-end circuit synthesis and execution time from 67 minutes to 2.5 minutes. The integration utilizes NVIDIA AI infrastructure to enable parallelized execution of quantum simulations, allowing for the exploration of large-scale circuits. This reduction in execution time supports shortened iteration cycles for testing and refining hybrid quantum-classical algorithms across various simulators and emerging quantum hardware.
The Classiq platform uses synthesis technology to transform functional models into optimized code compatible with multiple hardware backends, including GPUs and neutral-atom or superconducting processors. By incorporating CUDA-Q, the platform provides memory optimization and synthesis tools to evaluate quantum-ready methods within modern HPC pipelines. This hybrid environment allows researchers to establish the performance of algorithms before deployment on physical hardware. The workflow is intended to support the operationalization of quantum applications across major hyperscalers and hardware providers without requiring manual, low-level gate programming.
For further technical details on the IQAE benchmark and CUDA-Q integration, consult the official Classiq announcement here.
March 16, 2026
