Engineering
Ultrasound FPGA Accumulators: Preserve Headroom Before Cutting Precision
A short engineering review of fixed-point headroom in ultrasound FPGA channel accumulation, with a reproducible integer bound and explicit precision, overflow and validation limits.
By ALEVA | California, USA
How wide should a delay-and-sum accumulator be before an ultrasound OEM team considers reducing precision?
Separate range from precision
A June 2026 manuscript by Usman and colleagues explores most-significant-digit-first channel accumulation, allowing computation to stop before processing every bit plane. We reviewed arXiv v1; its record reports acceptance at IEEE SOCC, but we did not verify a final proceedings version. It is not evidence of an ALEVA implementation.
Earlier peer-reviewed FPGA ultrasound work by Kou and colleagues (2023) also makes summing-network organization part of the implementation trade-off. Neither paper supplies a universal word length for a different acquisition chain.
A reproducible headroom check
Consider an illustrative, unweighted sum of 64 aligned, signed 12-bit integers, with no prior scaling or rounding. Each input lies between −2,048 and 2,047. The sum can therefore range from −131,072 to 131,008.
An 18-bit signed accumulator covers that entire range. A 17-bit accumulator does not. More generally, B + ceil(log2 N) bits are sufficient for an exact unweighted sum of N signed B-bit integers. This is a worst-case arithmetic bound, not an image-quality result or an ALEVA hardware specification.
Apply the bound to the actual summation inputs—not automatically to ADC resolution. Interpolation, apodization products, scaling and fractional-bit conventions may change the required format.
Make overflow behavior explicit
AMD's Vitis HLS UG1399 documentation, version 2026.1, distinguishes quantization from overflow handling. It lists truncation and wraparound as defaults for ap_fixed; saturation or alternative rounding can require additional hardware. Choosing a type is therefore not the same as demonstrating acceptable numerical behavior.
Our proposed OEM acceptance test
Check coherent full-scale sums, alternating signs, representative channel recordings and strong reflectors against a wider reference. Count overflows and saturation events before evaluating any reduced-precision output.
Then compare point-target profiles, sidelobes and weak-echo retention using matched data and fixed display settings. Record resource use, achieved timing and end-to-end energy on the intended hardware. A favorable reconstruction image alone cannot establish safe headroom or complete-system efficiency.
Bottom line: establish range first, then evaluate precision. The integer example and acceptance checks above are engineering analysis and proposed tests—not measured ALEVA performance or clinical validation.
Sources and review boundary
Usman M, Khan S, Merhof D. Dynamic Ultrasound Beamforming Using Left-to-Right Arithmetic Adders on FPGA. arXiv v1, June 30, 2026. Reviewed manuscript; DOI: 10.48550/arXiv.2606.31490. Conference acceptance is reported by the authors; the reviewed source is the arXiv manuscript.
Kou Z et al. High-Level Synthesis Design of Scalable Ultrafast Ultrasound Beamformer With Single FPGA. IEEE TBCAS 17(3):446–457, June 2023. DOI: 10.1109/TBCAS.2023.3267614; Publication record and abstract.
AMD. Vitis HLS User Guide UG1399, Fixed-Point Identifier Summary. Version 2026.1, accessed October 17, 2026. Official documentation.
Source scope: the 2026 manuscript's relevant methods and limitations, AMD's fixed-point documentation, and the 2023 publication record/abstract. No independent FPGA synthesis, clinical validation or reproduced research figures are presented.