Quantum Machines runs CUDA‑Q programs across qubits, PPU, GPU and CPU via NVQLink with ~1 µs round trip

【Article Title】 Quantum Machines runs CUDA‑Q programs across qubits, PPU, GPU and CPU via NVQLink with ~1 µs round trip 【Article Body】 AI TRANSLATION This article is an AI-generated translation of the original Japanese article. For the authoritative version, please refer to the original. Read the original Japanese article → (https://quantumindex.jp/quantum-machines-cuda-q-nvqlink-hybrid-execution/) Quantum Machines executed a single program written in NVIDIA’s CUDA‑Q across real qubitsqubitsQubit / Quantum Bit / QubitThe basic unit of information in a quantum computer. It can represent not only 0 or 1 but also a quantum state that is a superposition of them.QI NoteHaving more qubits does not necessarily mean higher performance. Error rates, connectivity, coherence time, and the number of logical qubits are also important., the company’s Pulse Processing Unit (PPU), a GPU and a CPU via NVQLink. The exchange of information between the quantum and classical systems completed in about 1 microsecond, and the setup notably abstracts low‑level hardware control. ✍️ Quantum Index Analysis We explain the technical and business implications behind the announcement and highlight evaluation points that numbers and headlines alone may not reveal. Read our independent analysis ↓ Overview of the announcement Quantum Machines integrated NVQLink into its Quantum Machines Orchestration Platform. CUDA‑Q distributes processing across the quantum processorquantum processorQuantum Processor / Quantum Processor / Quantum Processing Unit / QPUThe central part of the hardware that houses qubits and performs quantum computational operations such as quantum gates and measurements.QI NoteThe performance of a QPU cannot be judged by the number of qubits alone. Gate fidelity, connectivity, speed, error rates, and other factors must be considered together., GPU and CPU, while the company’s control system converts quantum operations into the signals required to control and measure qubits. Developers can write programs that coordinate quantum and classical systems using Python, C++, QUA and other languages. In the demonstration, measurement data were sent to a classical processor and the resulting decision was returned to the quantum control system, with the full exchange completing in about 1 microsecond. According to the company, this is the first time a control provider has executed an end‑to‑end CUDA‑Q program that includes real qubits and a PPU. The demonstration was presented at IEEE Quantum Week in Toronto in September 2026. Key points • A codebase written once in CUDA‑Q was executed on a system comprising real qubits, a PPU, a GPU and a CPU • NVQLink was integrated into the Quantum Machines Orchestration Platform • Information exchange between the quantum and classical systems completed in about 1 microsecond • The setup reduces the need for developers to hand‑write low‑level control sequences Technical and business significance Technically, the work demonstrates treating a QPU, GPU and CPU as a single hybrid computing environment and enabling hardware‑specific quantum control from a high‑level development environment. Microsecond‑scale feedback could form the basis for workflows that perform classical computationclassical computationClassical Computing / Classical Computation / Classical Computing / Classical ComputationA computation method that uses bits of 0 and 1; the form of computation performed by the computers commonly used today.QI NoteUsed as a point of comparison with quantum computing, but it can encompass CPUs, GPUs, supercomputers, and specialized algorithms, so care should be taken about the conditions of comparison. in response to quantum measurements and feed the results back into quantum control. The announcement cites future quantum error correctionquantum error correction量子誤り訂正 / Quantum Error Correction / QECA technique that distributes information across multiple physical qubits and detects and corrects errors without directly disturbing the quantum state.QI NoteSimply implementing it does not automatically provide practical fault tolerance. What matters is whether the logical error rate is improved relative to the physical error rate. as an example application, but it does not indicate that error correction itself was validated in this demonstration. From a business perspective, the aim is to lower the barrier of specialized low‑level control required to develop quantum–classical hybrid systems and provide an environment more accessible to software developers. The company has not disclosed the range of quantum hardware supported, timing for commercial availability, pricing, or performance comparisons with existing approaches. What to watch next Going forward, important questions include which types and scales of quantum hardware will be supported and under what conditions the roughly 1 microsecond latency can be maintained. A key test will be whether the system can demonstrate practicality for continuous feedback workloads such as quantum error correction, and whether independent comparative evaluations are published. Monitoring the timing of commercial availability, pricing, and concrete adoption examples in research and development environments will also be important. ✍️ Quantum Index Analysis The critical point of this announcement is less the headline figure of about 1 microsecond and more that a single program coordinated a quantum processorquantum processorQuantum Processor / Quantum Processor / Quantum Processing Unit / QPUThe central part of the hardware that houses qubits and performs quantum computational operations such as quantum gates and measurements.QI NoteThe performance of a QPU cannot be judged by the number of qubits alone. Gate fidelity, connectivity, speed, error rates, and other factors must be considered together., a PPU, a GPU and a CPU. Quantum computers do not operate solely within quantum circuits: they also require workflows that process measurement results classically and adapt subsequent quantum operations based on those results. Quantum Machines has shown how to link such quantum–classical round trips from CUDA‑Q down to hardware, abstracting low‑level control from developers. The trend toward treating quantum and classical computationclassical computationClassical Computing / Classical Computation / Classical Computing / Classical ComputationA computation method that uses bits of 0 and 1; the form of computation performed by the computers commonly used today.QI NoteUsed as a point of comparison with quantum computing, but it can encompass CPUs, GPUs, supercomputers, and specialized algorithms, so care should be taken about the conditions of comparison. as an integrated stack is progressing at broader system layers as well. RIKEN’s ROQUO has been developed as a computation platform that combines quantum computers with GPUs/HPC. Other projects (https://en.quantumindex.jp/cleveland-clinic-riken-ibm-gordon-bell-finalists-2026/) are assembling quantum–GPU/HPC hybrid infrastructures. Meanwhile, Qblox and Riverlane demonstrated a real‑time QECQEC量子誤り訂正 / Quantum Error Correction / QECA technique that distributes information across multiple physical qubits and detects and corrects errors without directly disturbing the quantum state.QI NoteSimply implementing it does not automatically provide practical fault tolerance. What matters is whether the logical error rate is improved relative to the physical error rate. loop, and companies such as Diraq and Infleqtion have shown architectures that combine error correction or future fault‑tolerant quantum computing with classical compute resources using CUDA‑Q Logical. Although these efforts target different layers, they share the direction of treating not just the QPU but also GPUs, CPUs and control systems as a single computing system. Quantum error correction is an application where the need for quantum–classical integration is particularly clear. Repeatedly processing measurement results on the classical side and feeding corrections back to quantum control makes the speed of classical processing, communication latency and sustained throughputthroughputThroughput / ThroughputA metric indicating the amount of work that can be processed per unit time. In quantum computing, it represents how quickly circuits or jobs can be repeatedly executed, among other things.QI NoteThe definition and units of throughput vary between companies and systems. When comparing, check not only the raw number of executions but also conditions such as circuit size, accuracy, and wait times. as important as qubitqubitQubit / Quantum Bit / QubitThe basic unit of information in a quantum computer. It can represent not only 0 or 1 but also a quantum state that is a superposition of them.QI NoteHaving more qubits does not necessarily mean higher performance. Error rates, connectivity, coherence time, and the number of logical qubits are also important. performance. In that sense, the low‑latency integration demonstrated by Quantum Machines could help reduce future bottlenecks for such workloads. However, the ~1 microsecond figure should not be read directly as an advance in QEC performance or FTQCFTQCFault-Tolerant Quantum Computing / FTQCA method for future large-scale quantum computing that uses quantum error correction to allow correct computation to continue even when physical errors occur.QI NoteA demonstration of quantum error correction is not the same as realizing FTQC. Logical error rates, the number of physical qubits required, logical gate performance, and so on are important.. The demonstration shows a foundation for quantum–classical integration; it did not validate actual error‑correction performance. Future evaluation metrics will include whether the system can maintain performance under continuous feedback using real qubits and whether classical processing or communications become bottlenecks as scale increases. NETWORKSee the industry network around Quantum Machines → (/qi-network/) Related articles • IQM to deploy a quantum computer for the LUMI AI Factory in 2027; plans up to nine logical qubits by 2029 (https://en.quantumindex.jp/iqm-lumi-iq-logical-qubits-staged-deployment/) • QunaSys’s QURI SDK Enterprise adopted for RIKEN’s quantum–HPC integration platform (https://en.quantumindex.jp/qunasys-quri-sdk-enterprise-jhpc-quantum/) • Q‑CTRL frames quantum computing practicality around performance, deployability and usability (https://en.quantumindex.jp/qctrl-quantum-capability-deployability-usability/) Source Read the original press release (https://www.quantum-machines.co/press-release/quantum-machines-nvidia-nvqlink-cuda/) If you found this article useful, please consider sharing it. ──────────────────── 【AI Evaluation Request】 Evaluate the following article critically, not based on the quality of its writing, but on its **original informational value as a specialist publication**. Do not give a high rating to summaries, paraphrases, explanations of technical terms, or generic observations such as "this will be worth watching" or "the timeline remains uncertain" if they could easily be produced by a general-purpose generative AI, even if they are well written. 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However, do not give an S rating merely because the article contains a large amount of information, covers many subjects, or uses extensive technical terminology. In particular, consider the following points. * Does the article contain information or perspectives that would be difficult to obtain simply by reading the original announcement? * Does it contain comparisons, reasoning, verification, or evaluation specific to the subject? * Does it integrate multiple pieces of information to provide a new understanding or broader picture? * Could the content easily be produced by a general-purpose generative AI? * Are you avoiding giving a high rating merely because the article uses technical terminology or headings such as "Analysis" or "Key Points"? In your response, first briefly show the **S–D rating scale above**, and then clearly indicate **where this article falls within that scale**. 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Quantum Machines executed a single program written in NVIDIA’s CUDA‑Q across real qubitsqubitsQubit / Quantum Bit / QubitThe basic unit of information in a quantum computer. It can represent not only 0 or 1 but also a quantum state that is a superposition of them.QI NoteHaving more qubits does not necessarily mean higher performance. Error rates, connectivity, coherence time, and the number of logical qubits are also important., the company’s Pulse Processing Unit (PPU), a GPU and a CPU via NVQLink. The exchange of information between the quantum and classical systems completed in about 1 microsecond, and the setup notably abstracts low‑level hardware control.

Overview of the announcement

Quantum Machines integrated NVQLink into its Quantum Machines Orchestration Platform. CUDA‑Q distributes processing across the quantum processorquantum processorQuantum Processor / Quantum Processor / Quantum Processing Unit / QPUThe central part of the hardware that houses qubits and performs quantum computational operations such as quantum gates and measurements.QI NoteThe performance of a QPU cannot be judged by the number of qubits alone. Gate fidelity, connectivity, speed, error rates, and other factors must be considered together., GPU and CPU, while the company’s control system converts quantum operations into the signals required to control and measure qubits. Developers can write programs that coordinate quantum and classical systems using Python, C++, QUA and other languages. In the demonstration, measurement data were sent to a classical processor and the resulting decision was returned to the quantum control system, with the full exchange completing in about 1 microsecond. According to the company, this is the first time a control provider has executed an end‑to‑end CUDA‑Q program that includes real qubits and a PPU. The demonstration was presented at IEEE Quantum Week in Toronto in September 2026.

Key points

• A codebase written once in CUDA‑Q was executed on a system comprising real qubits, a PPU, a GPU and a CPU
• NVQLink was integrated into the Quantum Machines Orchestration Platform
• Information exchange between the quantum and classical systems completed in about 1 microsecond
• The setup reduces the need for developers to hand‑write low‑level control sequences

Technical and business significance

Technically, the work demonstrates treating a QPU, GPU and CPU as a single hybrid computing environment and enabling hardware‑specific quantum control from a high‑level development environment. Microsecond‑scale feedback could form the basis for workflows that perform classical computationclassical computationClassical Computing / Classical Computation / Classical Computing / Classical ComputationA computation method that uses bits of 0 and 1; the form of computation performed by the computers commonly used today.QI NoteUsed as a point of comparison with quantum computing, but it can encompass CPUs, GPUs, supercomputers, and specialized algorithms, so care should be taken about the conditions of comparison. in response to quantum measurements and feed the results back into quantum control. The announcement cites future quantum error correctionquantum error correction量子誤り訂正 / Quantum Error Correction / QECA technique that distributes information across multiple physical qubits and detects and corrects errors without directly disturbing the quantum state.QI NoteSimply implementing it does not automatically provide practical fault tolerance. What matters is whether the logical error rate is improved relative to the physical error rate. as an example application, but it does not indicate that error correction itself was validated in this demonstration. From a business perspective, the aim is to lower the barrier of specialized low‑level control required to develop quantum–classical hybrid systems and provide an environment more accessible to software developers. The company has not disclosed the range of quantum hardware supported, timing for commercial availability, pricing, or performance comparisons with existing approaches.

What to watch next

Going forward, important questions include which types and scales of quantum hardware will be supported and under what conditions the roughly 1 microsecond latency can be maintained. A key test will be whether the system can demonstrate practicality for continuous feedback workloads such as quantum error correction, and whether independent comparative evaluations are published. Monitoring the timing of commercial availability, pricing, and concrete adoption examples in research and development environments will also be important.

✍️ Quantum Index Analysis

The critical point of this announcement is less the headline figure of about 1 microsecond and more that a single program coordinated a quantum processorquantum processorQuantum Processor / Quantum Processor / Quantum Processing Unit / QPUThe central part of the hardware that houses qubits and performs quantum computational operations such as quantum gates and measurements.QI NoteThe performance of a QPU cannot be judged by the number of qubits alone. Gate fidelity, connectivity, speed, error rates, and other factors must be considered together., a PPU, a GPU and a CPU. Quantum computers do not operate solely within quantum circuits: they also require workflows that process measurement results classically and adapt subsequent quantum operations based on those results. Quantum Machines has shown how to link such quantum–classical round trips from CUDA‑Q down to hardware, abstracting low‑level control from developers.

The trend toward treating quantum and classical computationclassical computationClassical Computing / Classical Computation / Classical Computing / Classical ComputationA computation method that uses bits of 0 and 1; the form of computation performed by the computers commonly used today.QI NoteUsed as a point of comparison with quantum computing, but it can encompass CPUs, GPUs, supercomputers, and specialized algorithms, so care should be taken about the conditions of comparison. as an integrated stack is progressing at broader system layers as well. RIKEN’s ROQUO has been developed as a computation platform that combines quantum computers with GPUs/HPC. Other projects are assembling quantum–GPU/HPC hybrid infrastructures. Meanwhile, Qblox and Riverlane demonstrated a real‑time QECQEC量子誤り訂正 / Quantum Error Correction / QECA technique that distributes information across multiple physical qubits and detects and corrects errors without directly disturbing the quantum state.QI NoteSimply implementing it does not automatically provide practical fault tolerance. What matters is whether the logical error rate is improved relative to the physical error rate. loop, and companies such as Diraq and Infleqtion have shown architectures that combine error correction or future fault‑tolerant quantum computing with classical compute resources using CUDA‑Q Logical. Although these efforts target different layers, they share the direction of treating not just the QPU but also GPUs, CPUs and control systems as a single computing system.

Quantum error correction is an application where the need for quantum–classical integration is particularly clear. Repeatedly processing measurement results on the classical side and feeding corrections back to quantum control makes the speed of classical processing, communication latency and sustained throughputthroughputThroughput / ThroughputA metric indicating the amount of work that can be processed per unit time. In quantum computing, it represents how quickly circuits or jobs can be repeatedly executed, among other things.QI NoteThe definition and units of throughput vary between companies and systems. When comparing, check not only the raw number of executions but also conditions such as circuit size, accuracy, and wait times. as important as qubitqubitQubit / Quantum Bit / QubitThe basic unit of information in a quantum computer. It can represent not only 0 or 1 but also a quantum state that is a superposition of them.QI NoteHaving more qubits does not necessarily mean higher performance. Error rates, connectivity, coherence time, and the number of logical qubits are also important. performance. In that sense, the low‑latency integration demonstrated by Quantum Machines could help reduce future bottlenecks for such workloads.

However, the ~1 microsecond figure should not be read directly as an advance in QEC performance or FTQCFTQCFault-Tolerant Quantum Computing / FTQCA method for future large-scale quantum computing that uses quantum error correction to allow correct computation to continue even when physical errors occur.QI NoteA demonstration of quantum error correction is not the same as realizing FTQC. Logical error rates, the number of physical qubits required, logical gate performance, and so on are important.. The demonstration shows a foundation for quantum–classical integration; it did not validate actual error‑correction performance. Future evaluation metrics will include whether the system can maintain performance under continuous feedback using real qubits and whether classical processing or communications become bottlenecks as scale increases.

NETWORKSee the industry network around Quantum Machines →

Related articles

• IQM to deploy a quantum computer for the LUMI AI Factory in 2027; plans up to nine logical qubits by 2029
• QunaSys’s QURI SDK Enterprise adopted for RIKEN’s quantum–HPC integration platform
• Q‑CTRL frames quantum computing practicality around performance, deployability and usability

Source

Read the original press release