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Pasqal and NVIDIA Integrate CUDA-Q for Slurm-Native HPC Workflows

Quantum Computing Report
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⚡ Quantum Brief
Pasqal and NVIDIA integrated CUDA-Q with Pasqal’s Quantum Resource Management Interface (QRMI), enabling quantum processors to operate as native accelerators in HPC environments using Slurm, the standard job scheduler. The integration allows researchers to manage quantum jobs alongside classical CPU/GPU workloads, reducing adoption barriers by embedding quantum routines into existing HPC workflows without operational disruption. CUDA-Q enables tight coupling of GPU-accelerated classical code with quantum routines, while QRMI automates QPU provisioning, authentication, and monitoring, supporting hybrid quantum-GPU supercomputing for optimization, simulation, and AI. The first on-premises deployment will occur at Italy’s CINECA supercomputing center, integrating Pasqal’s QPU with the Leonardo pre-exascale system for Slurm-native hybrid workloads, with cloud access already available. This milestone aligns with Pasqal’s planned public listing via Bleichroeder Acquisition Corp. II, aiming to standardize hybrid HPC-quantum capabilities in modern supercomputing infrastructure.
Pasqal and NVIDIA Integrate CUDA-Q for Slurm-Native HPC Workflows

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Pasqal and NVIDIA Integrate CUDA-Q for Slurm-Native HPC Workflows Pasqal has announced the integration of the NVIDIA CUDA-Q platform with its Quantum Resource Management Interface (QRMI) runtime, enabling quantum processors to function as native accelerators within standard High-Performance Computing (HPC) environments. This integration allows CUDA-Q workloads to be scheduled and orchestrated on Pasqal’s neutral-atom systems using Slurm, the industry-standard job submission and resource management tool. By exposing the Quantum Processing Unit (QPU) as a schedulable resource alongside CPUs and GPUs, the system reduces adoption friction for researchers who can now manage quantum jobs within their existing operational workflows. The technical framework for this integration relies on QRMI, a hardware-agnostic interface originally established by IBM in collaboration with Pasqal, Rensselaer Polytechnic Institute (RPI), and the STFC Hartree Centre. CUDA-Q facilitates the tight interleaving of GPU-accelerated classical kernels with quantum routines, while QRMI handles the automated provisioning, secure authentication, and monitoring of the QPU during execution. This setup enables heterogeneous “quantum-GPU supercomputing” where quantum routines are invoked as part of a larger classical job, providing a practical pathway for scaling applications in optimization, simulation, and AI. The first on-premises deployment of this stack is scheduled for CINECA in Italy, where Pasqal’s QPU will be integrated with the Leonardo pre-exascale supercomputer to enable Slurm-native hybrid workloads. The integration is already available for users accessing Pasqal’s systems via the cloud. This milestone occurs alongside Pasqal’s ongoing path to go public through a business combination with Bleichroeder Acquisition Corp. II, aiming to establish production-grade hybrid HPC–quantum capabilities as a standard feature of modern supercomputing centers. For further technical details on the QRMI implementation and the CINECA deployment, consult the official Pasqal newsroom announcement here. March 16, 2026 Mohamed Abdel-Kareem2026-03-16T17:33:34-07:00 Leave A Comment Cancel replyComment Type in the text displayed above Δ This site uses Akismet to reduce spam. Learn how your comment data is processed.

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Source: Quantum Computing Report