Predictive Window Decoding for Fault-Tolerant Quantum Programs

TL;DR

This paper introduces a speculative window decoding scheme for fault-tolerant quantum programs, significantly reducing runtime by predicting data dependencies and enabling parallel decoding, thus improving efficiency in real-time quantum error correction.

Contribution

It proposes a novel speculative decoding method inspired by classical branch prediction, enhancing parallelism and reducing runtime in quantum error correction.

Findings

Speculation reduces application runtimes by 40% on average.

The scheme enables multiple decoding layers to be resolved simultaneously.

It maintains accuracy while improving decoding speed.

Abstract

Real-time decoding is a key ingredient in future fault-tolerant quantum systems, yet many decoders are too slow to run in real time. Prior work has shown that parallel window decoding schemes can scalably meet throughput requirements in the presence of increasing decoding times, given enough classical resources. However, windowed decoding schemes require that some decoding tasks be delayed until others have completed, which can be problematic during time-sensitive operations such as T gate teleportation, leading to suboptimal program runtimes. To alleviate this, we introduce a speculative window decoding scheme. Taking inspiration from branch prediction in classical computer architecture our decoder utilizes a light-weight speculation step to predict data dependencies between adjacent decoding windows, allowing multiple layers of decoding tasks to be resolved simultaneously. Through a state-of-the-art compilation pipeline and a detailed simulator, we find that speculation reduces application runtimes by 40% on average compared to prior parallel window decoders.