Insider Brief
- memQ announced a roadmap for its Extensible Distributed Quantum Compiler (xDQC), a system designed to distribute quantum workloads across multiple quantum processors using the CUDA-Q platform from NVIDIA.
- The compiler profiles workloads across available qubit resources, evaluates routing and compute assignments, and distributes tasks across interconnected quantum processors based on performance and resource utilization.
- memQ said the CUDA-Q–based xDQC platform is expected to be available for preview in the first half of 2026 and will complement the company’s xQNA quantum networking hardware portfolio.
PRESS RELEASE — memQ™, the industry leader in quantum networking solutions for distributed quantum computing, announced today the roadmap for their Extensible Distributed Quantum Compiler (xDQC), built upon the NVIDIA CUDA-Q platform. This novel approach to quantum workload distribution allows workloads to be distributed across multiple quantum processors in a system or a network, based upon qubit modality and availability, to achieve significantly higher throughput for the most demanding problems.
Quantum computing is the next major shift in computing, forecasted to become a $100B market by 2035 according to McKinsey & Company. Of that, the quantum communications subsector alone is projected to reach up to $15B. Key workloads include distributed quantum computing and blind quantum cloud computing, each of which requiring the ability to execute circuits and gates across a quantum network based upon unique properties of the workload as well as the system resources available to it. “We see the emergence of a ‘right qubit for the right task’ paradigm which leverages systems of different qubit modalities – and possibly different vendors – as quantum workloads increase,” stated Andre Konig, CEO of Global Quantum Intelligence. “This aligns with DARPA’s position that by leveraging advances in photonic integration, quantum interconnects, and quantum circuit design, we have the potential to overcome the current scaling and performance bottlenecks in quantum systems.”
The memQ xDQC solution is a network-and hardware-aware orchestration layer that treats QPU-QPU links in quantum circuits as first-class components of the quantum equation that can be optimized for scale and performance. The xDQC allows users to profile a workload across qubit resources available, evaluate various routing and computational assignments, and select the one with optimum performance and resource utilization. The simulation recommendations are based upon hardware-aware noise models which simulate real interconnect conditions – essentially a “digital twin” of distributed quantum processors in a physical network. Once selected, the compiler can assign workload tasks to various QPUs for execution, then recompile the individual responses for a total result with greater performance and ROI than a monolithic approach.
“The industry approach to ‘scale’ is shifting from monolithic architectures – which will find a hard ‘ceiling’ – to modular, distributed computing. And the missing piece in scaling isn’t just adding more qubits, it’s leveraging the complex networks that connect them to unlock new applications. We’re building
a full-stack simulation toolkit that lets researchers co-design hardware and architecture for distributed quantum systems at scale.” said Sean Sullivan, CTO of memQ. “We chose CUDA-Q as the foundation for this solution due to its open ecosystem, backend flexibility, and GPU-accelerated simulation capabilities that allow us to profile key dynamics such as modality, circuit type, topology, and resource loads in a comprehensive way. By making it open source, we’re opening the ability to co-design at scale to the entire community.”
“CUDA-Q is built to support developing workloads for at-scale hybrid quantum-classsical systems”, said Sam Stanwyck, Director of Quantum Product at NVIDIA. “memQ’s use of CUDA-Q to provide access to QPU-to-QPU interconnected systems is a key step towards scaling and integrating quantum processors to work with tomorrow’s supercomputers.”
memQ’s xDQC will complement the company’s xQNA portfolio which includes chip-scale solutions for quantum network interface controllers (QNICs), quantum memory modules (QMMs), and quantum control systems (QCS). The CUDA-Q based xDQC is expected to be available for preview in the first half of 2026.
