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AFS: Accurate, Fast, and Scalable Error-Decoding for Fault-Tolerant Quantum Computers

Das, Poulami and Pattison, Christopher A. and Manne, Srilatha and Carmean, Douglas M. and Svore, Krysta M. and Qureshi, Moinuddin and Delfosse, Nicolas (2022) AFS: Accurate, Fast, and Scalable Error-Decoding for Fault-Tolerant Quantum Computers. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA). IEEE , Piscataway, NJ, pp. 259-273. ISBN 978-1-6654-2027-3.

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Quantum computers promise computational advantages for many important problems across various application domains. Unfortunately, physical quantum devices are highly susceptible to errors that limit us from running most of these quantum applications. Quantum Error Correction (QEC) codes are required to implement Fault-Tolerant Quantum Computers (FTQC) on which computations can be performed without encountering errors. Error decoding is a critical component of quantum error correction and is responsible for transforming a set of qubit measurements generated by the QEC code, called the syndrome, into error locations and error types. For the feasibility of implementation, error decoders must not only identify errors with high accuracy, but also be fast and scalable to a large number of qubits. Unfortunately, most of the prior works on error decoding have focused primarily only on the accuracy and have relied on software implementations that are too slow to be of practical use. Furthermore, these studies only look at designing a single decoder and do not analyze the challenges involved in scaling the storage and bandwidth requirements when performing error correction in large systems with thousands of qubits.In this paper, we present AFS, an accurate, fast, and scalable decoder architecture that is designed to operate in the context of systems with hundreds of logical qubits. We present the hardware implementation of AFS, which is based on the Union Find decoding algorithm and employs a three-stage pipelined design. AFS provides orders of magnitude higher accuracy compared to recent SFQ-based hardware decoders (logical error rate of 6×10⁻¹⁰ for physical error rate of 10⁻³) and low decoding latency (42ns on average), while being robust to measurement errors introduced while extracting syndromes during the QEC cycles. We also reduce the amount of decoding hardware required to perform QEC simultaneously on all the logical qubits by co-designing the micro-architecture across multiple decoding units. Our proposed Conjoined-Decoder Architecture (CDA) reduces the storage overhead by 70% (10MB to 2.8MB). Finally, we reduce the bandwidth overheads required to transmit syndromes from the qubits to the decoders by exploiting the sparsity in the syndromes and compressing the data. Our proposed Syndrome Compression reduces the bandwidth requirement by 30x, on an average.

Item Type:Book Section
Related URLs:
URLURL TypeDescription Paper
Pattison, Christopher A.0000-0003-0118-5257
Svore, Krysta M.0000-0001-9500-9443
Qureshi, Moinuddin0000-0002-1314-9096
Delfosse, Nicolas0000-0002-3949-981X
Alternate Title:A Scalable Decoder Micro-architecture for Fault-Tolerant Quantum Computing
Additional Information:© 2022 IEEE. An earlier version of this paper was uploaded on arXiv [25] in January 2020. We thank the reviewers of HPCA-2020, ISCA-2020, ISCA-2021, MICRO-2021, and HPCA-2022 for their comments and feedback. We also thank Dave Wecker, Dave Probert, Michael Beverland, and Helmut Katzgraber for the technical discussions. Poulami Das was supported by the Microsoft PhD fellowship.
Funding AgencyGrant Number
Subject Keywords:Quantum computing, Quantum error correction, Fault-tolerant quantum computing, Decoding, Union-Find decoding, Surface codes
Record Number:CaltechAUTHORS:20220629-469307900
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Official Citation:P. Das et al., "AFS: Accurate, Fast, and Scalable Error-Decoding for Fault-Tolerant Quantum Computers," 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2022, pp. 259-273, doi: 10.1109/HPCA53966.2022.00027
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:115297
Deposited By: Tony Diaz
Deposited On:30 Jun 2022 15:57
Last Modified:30 Jun 2022 15:57

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