Triage: An Adaptive Parallel Window Decoding Scheduler for Real-time Fault-Tolerant Quantum Computation

TL;DR

Triage is an adaptive scheduling architecture for real-time quantum decoding that reduces logical error rates and prevents operation stalls in fault-tolerant quantum computing.

Contribution

It introduces a dual-mode, resource-aware scheduler that dynamically allocates decoders to improve decoding efficiency and fault tolerance.

Findings

Achieves 52.6% average reduction in logical error rate

Maintains low operation stalls and error rates under resource constraints

Outperforms standard temporal parallelism in benchmarks

Abstract

Fault-tolerant quantum computation (FTQC) critically depends on real-time classical decoding, which is rapidly emerging as a system bottleneck. As quantum systems scale, decoding latency and throughput limitations lead to exponential syndrome backlogs and logical operation stalls. While hardware accelerators and parallel windowing offer pathways to speed up decoding, dynamically deploying a finite pool of decoders across a vast quantum error correction architecture remains an unresolved resource allocation problem. To address this, we formulate FTQC decoding as a constrained dynamic scheduling problem by utilizing a spatio-temporal framework based on slices. We propose Triage, a dual-mode architecture that mitigates operation stalls by adaptively combining a cost-efficient heuristic scheduler with a priority-aware emergency mode to rapidly resolve the causal cone of critical operations. Our evaluation shows that Triage maintains low algorithm stalls and logical error rates even under scarce classical resource constraints. Across various benchmarks, Triage achieves an average logical error rate reduction of 52.6% compared to standard temporal parallelism, enabling an efficient classical control plane for scalable FTQC architectures.