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For real-time quantum computing

Low-latency control–GPU interconnect module

Connect quantum control and GPU computing in a real-time feedback path.

Designed for real-time processing and error correction in superconducting quantum computing. FPGA-based protocol conversion, data organization and result return provide a bidirectional connection between control electronics and GPU servers.

Discuss integrationView specifications
Control electronicsMeasurement data / feedback control
LVDS / Aurora
RFSoC interconnectProtocol conversion · timestamps · buffering
100G RDMA
GPU serverRegistered memory / GPU compute tasks
Conceptual architecture, not measured performance. Direct RDMA access to GPU memory is not assumed.
Control-side adaptation
LVDS / Aurora
Server-side link specification
100G RDMA
Data uplink and result return
Bidirectional feedback

Who it is for：Quantum control engineering teams / Real-time QEC algorithm teams / System integration teams

Core capabilities

From data input to result return

  1. Connect existing control platforms

    Adapt LVDS or Aurora to the peer control protocol and normalize data from different sources.

  2. Establish a bidirectional data path

    Use 100G RDMA to transfer measurement data to registered server memory and return processing results.

  3. Organize real-time data streams

    Handle timestamps, data alignment, queue scheduling, buffering and flow control in the FPGA.

  4. Support integration and development

    Agree on configuration tools, communication interfaces, reference designs and development documentation for each project.

Technical specifications

Technical specifications

Low-latency control–GPU interconnect module — Technical specifications
ItemConfiguration and capabilities
Core platformAMD Zynq UltraScale+ RFSoC XCZU47DR
Control-side interfacesLVDS / Aurora, adapted to the peer protocol
Server-side interface100G Ethernet / RDMA / RoCE
Data directionMeasurement uplink and processing-result return
FPGA processingProtocol conversion, framing, timestamps, buffering and flow control
Effective bandwidth and latencySubject to the delivered configuration and test report

100G is a link specification, not measured effective throughput. Interfaces, bandwidth and end-to-end latency depend on the delivered configuration and test report.

Optional: RF signal generation and acquisition

RFSoC RF capabilities may support control-system integration and signal-processing validation. Exposed channels, sample rates, RF range and firmware support require separate confirmation; chip resource limits are not standard delivery guarantees.

Applications

Built around quantum computing workflows

  1. Real-time quantum error correction

    Transfer state-discrimination results or syndrome data to decoding tasks on the server and return processing results to the control electronics.

  2. Add GPU computing to existing control platforms

    Connect existing control equipment with GPU computing through protocol adaptation and a data path for state analysis, parameter optimization and control tasks.

  3. Integration and algorithm validation

    Validate interfaces, timing and data processing. RF integration is available only when supported by the agreed configuration.

Application scenarios, not customer delivery case studies.

Integration workflow

Start with your system requirements

  1. Define interfaces and workloads

    Align control protocols, data formats and the server environment.

  2. Agree on integration and testing

    Define workloads, latency measurement boundaries and acceptance criteria.

  3. Confirm configuration and delivery

    Agree on the module, firmware, software interfaces and development documentation.

Start a technical conversation

Connect your control platform to GPU real-time processing

Bring your interfaces, server environment and feedback requirements to discuss adaptation, test criteria and delivery configuration.

Discuss integration