Papers for
fpga developers
Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.
GarageWorks enables unified FPGA and software testing with shared testbench
GarageWorks: A Shared Testbench Abstraction for Software Simulation and FPGA Testing
Abstract: GarageWorks is a lightweight FPGA testing framework that enables the same cocotb testbench to be used for both software RTL simulation and FPGA-accelerated hardware simulation. A shared abstraction hides backend-specific interfaces, while synthesizable Advanced eXtensible Interface (AXI) dispatchers provide design-under-test (DUT)-specific control and test operations on the FPGA. GarageWorks is intended for rapid bare-metal testing of standalone designs and on-chip processing logic for scientific sensors, rather than full SoC-level prototyping. The framework has been validated on AMD Alveo V80 FPGAs with several internal designs and provides initial support for AI-assisted generation of DUT-specific test components.
Multi-wire SPI interface boosts data transfer for wearable ultrasound devices
Open-Source Multi-Wire SPI Readout for Wearable Ultrasound Probes
Abstract: Wearable ultrasound probes must transfer increasingly large acquisition payloads while maintaining compact, low-power electronics. In TinyProbe, the current bottleneck in data transfer occurs between the acquisition FPGA and the wireless system controller. This work presents an open-source, multi-wire SPI readout interface that uses serial command and address phases followed by a build-time-selectable dual- or quad-lane payload phase that is intended to address this bottleneck by increasing the potential bandwidth over the wifi limit while retaining compatibility with the Microcontroller-centric wearable US architecture. The interface emulates a serial flash memory, enabling compatibility with a broad range of microcontroller families and their existing peripheral interfaces. On the FPGA, the data path connects the existing acquisition FIFOs to the SPI interface through clock-domain crossing, sample reshaping, and packing into 32-bit words. Dual-SPI readout is integrated into the existing IGLOO2/SiWG917 TinyProbe architecture and verified at an SCLK frequency of 5 MHz. A separate Kria K26 testbed is used to characterize the FPGA SPI interface independently of the acquisition and wireless subsystems, demonstrating error-free transfers at SCLK frequencies up to 66 MHz. These measurements identify the SiWG917 multi-lane SPI implementation as the next bandwidth-limiting component and motivate a future upgrade of the system controller. The HDL and MCU implementations are released under a permissive open-source license.
Real-time flux correction boosts superconducting quantum gate accuracy
Precision and resource scaling of real-time flux distortion compensation for superconducting quantum control
Abstract: Real-time waveform generation supports dynamic quantum circuits without pre-storing complete waveforms for every execution path. However, long-lived distortions in flux-control lines degrade gate fidelity, requiring compensation to account for the actual pulse history. A frequency-domain inversion and time-domain fitting method is proposed for resource-efficient real-time flux distortion compensation. The method fits the reconstructed compensation impulse response with a compact hybrid infinite impulse response (IIR) and finite impulse response (FIR) filter. Look-ahead parallelization enables this filter to process synthesized waveforms at 1.2GSa/s on a field-programmable gate array (FPGA). Two-qubit cross-entropy benchmarking shows that real-time IIR filtering achieves a median controlled-Z Pauli fidelity close to the software-reference value of 99.57%. Numerical analysis and FPGA synthesis indicate approximately logarithmic growth in hardware resource use with compensation timescale. Extending compensation from microsecond to hundred-microsecond timescales increases look-up table (LUT) and digital signal processing (DSP) resource use by only about 14% and 4%, respectively, while maintaining a relative arithmetic error below $10^{-4}$. This work provides a scalable hardware foundation for high-fidelity flux control in dynamic superconducting quantum circuits.