Micro Blossom

Exact MWPM decoding with sub-microsecond latency

Micro Blossom is the first publicly known hardware-accelerated exact minimum-weight perfect matching (MWPM) decoder to achieve sub-microsecond decoding latency.

The FPGA prototype in our ASPLOS 2025 paper achieves 0.8 microseconds of average decoding latency for a distance-13 surface code at a physical error rate of 0.1%, running at 62 MHz. Sub-microsecond average latency is demonstrated up to distance 13 under these evaluated conditions.

This is latency, not just throughput: increasing throughput can keep pace with incoming syndrome measurements without reducing the time a dependent logical operation must wait for its correction. Micro Blossom accelerates the decoding response itself. It does not do the trick by dividing the decoding time by d rounds of syndrome extraction, which makes the data look better; rather, it faithfully report the overall latency from the last syndrome round to the time when the error-corrected logical readout becomes available. PS: The reported result is an average latency, not a worst-case guarantee for every sample.

Micro Blossom architecture maps a surface-code decoding graph to parallel vertex and edge processing units, connected to a controller and CPU.
Micro Blossom co-designs the decoding algorithm and a heterogeneous CPU/FPGA architecture, exploiting fine-grained parallelism at every vertex and edge. Figure from the Micro Blossom repository, copyright 2023 Yue Wu, used under the MIT license.

Exact decoding, hardware acceleration

The decoder retains the optimality of MWPM rather than replacing matching with an approximate heuristic. A parametrized accelerator handles massively parallel graph operations, while software handles more complex control and data structures. The implementation generates hardware for a supplied decoding graph.

Micro Blossom benchmark charts compare CPU and FPGA decoding latency distributions and the resulting effective logical error rates.
Latency distributions and their effect on logical errors, from the Micro Blossom repository. The distance-9 histograms illustrate the reduction in response latency; the distance-13 headline result above is from the ASPLOS paper. Copyright 2023 Yue Wu, MIT license.

See the paper for the architecture, correctness arguments, and evaluation, and the open-source implementation for the hardware and software.

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Yue Wu
Senior Researcher

I build algorithms, hardware, and systems for real-time quantum error correction at Microsoft Azure Quantum.