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Ferraz, O., Coutinho, B. C., Falcão, G., Gomes, M., Monteiro, F. A. & Silva, V. (2025). GPU-accelerated syndrome decoding for quantum LDPC codes below the 63 µs latency threshold. In Michael B. Matthews (Ed.), 2025 59th Asilomar Conference on Signals, Systems, and Computers (pp. 1878?1882). IEEE. https://doi.org/10.1109/IEEECONF67917.2025.11443687

Ó. Ferraz et al.,  "GPU-accelerated syndrome decoding for quantum LDPC codes below the 63 µs latency threshold", in 2025 59th Asilomar Conf. on Signals, Systems, and Computers, Michael B. Matthews, Ed.,  Pacific Grove, CA, USA, IEEE, 2025, pp. 1878-1882

@inproceedings{ferraz2025_1791884190354,
	author = "Ferraz, O. and Coutinho, B. C. and Falcão, G. and Gomes, M. and Monteiro, F. A. and Silva, V.",
	title = "GPU-accelerated syndrome decoding for quantum LDPC codes below the 63 µs latency threshold",
	booktitle = "2025 59th Asilomar Conference on Signals, Systems, and Computers",
	year = "2025",
	editor = "Michael B. Matthews",
	volume = "",
	number = "",
	series = "",
	doi = "10.1109/IEEECONF67917.2025.11443687",
	pages = "1878-1882",
	publisher = "IEEE",
	address = " Pacific Grove, CA, USA",
	organization = "IEEE",
	url = "https://ieeexplore.ieee.org/abstract/document/11443687"
}

TY  - CPAPER
TI  - GPU-accelerated syndrome decoding for quantum LDPC codes below the 63 µs latency threshold
T2  - 2025 59th Asilomar Conference on Signals, Systems, and Computers
AU  - Ferraz, O.
AU  - Coutinho, B. C.
AU  - Falcão, G.
AU  - Gomes, M.
AU  - Monteiro, F. A.
AU  - Silva, V.
PY  - 2025
SP  - 1878-1882
SN  - 1058-6393
DO  - 10.1109/IEEECONF67917.2025.11443687
CY  -  Pacific Grove, CA, USA
UR  - https://ieeexplore.ieee.org/abstract/document/11443687
AB  - This paper presents a GPU-accelerated decoder for quantum low-density parity-check (QLDPC) codes that achieves sub-63 µs latency, below the surface code decoder’s real-time threshold demonstrated on Google’s Willow quantum processor. While surface codes have demonstrated below-threshold performance, the encoding rates approach zero as code distances increase, posing challenges for scalability. Recently proposed QLDPC codes, such as those by Panteleev and Kalachev, offer constant-rate encoding and asymptotic goodness but introduce higher decoding complexity. To address such limitation, this work presents a parallelized belief propagation decoder leveraging syndrome information on commodity GPU hardware. Parallelism was exploited to maximize performance within the limits of target latency, allowing decoding latencies under 26 µs for [[784, 24, 24]] codes and as low as 16.9 µs for smaller codes, meeting the tight timing constraints of superconducting qubit cycles. These results show that real-time, scalable decoding of asymptotically good quantum codes is achievable using widely available commodity hardware, advancing the feasibility of fault-tolerant quantum computation beyond surface codes.
ER  -