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Taming the Instruction Bandwidth of Quantum Computers via Hardware-Managed Error Correction

机译:通过硬件管理纠错驯服量子计算机的指令带宽

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A quantum computer consists of quantum bits (qubits) and a control processor that acts as an interface between the programmer and the qubits. As qubits are very sensitive to noise, they rely on continuous error correction to maintain the correct state. Current proposals rely on software-managed error correction and require large instruction bandwidth, which must scale in proportion to the number of qubits. While such a design may be reasonable for small-scale quantum computers, we show that instruction bandwidth tends to become a critical bottleneck for scaling quantum computers. In this paper, we show that 99.999% of the instructions in the instruction stream of a typical quantum workload stem from error correction. Using this observation, we propose QuEST (Quantum Error-Correction Substrate), an architecture that delegates the task of quantum error correction to the hardware. QuEST uses a dedicated programmable micro-coded engine to continuously replay the instruction stream associated with error correction. The instruction bandwidth requirement of QuEST scales in proportion to the number of active qubits (typically <; <; 0.1%) rather than the total number of qubits. We analyze the effectiveness of QuEST with area and thermal constraints and propose a scalable microarchitecture using typical Quantum Error Correction Code (QECC) execution patterns. Our evaluations show that QuEST reduces instruction bandwidth demand of several key workloads by ftve orders of magnitude while ensuring deterministic instruction delivery. Apart from error correction, we also observe a large instruction bandwidth requirement for fault tolerant quantum instructions (magic state distillation). We extend QuEST to manage these instructions in hardware and provide additional reduction in bandwidth. With QuEST, we reduce the total instruction bandwidth by eight orders of magnitude.
机译:量子计算机由量子位(QUBits)和一个控制处理器组成,其充当程序员与QUBits之间的接口。由于Qubits对噪声非常敏感,因此它们依靠连续的误差校正来维持正确的状态。当前建议依赖于软件管理的纠错,并且需要大的指令带宽,必须与Qubits数量成比例缩放。虽然这种设计对于小型量子计算机可能是合理的,但我们表明指令带宽倾向于成为缩放量子计算机的临界瓶颈。在本文中,我们展示了典型量子工作负载指令流中的99.999%的指令源自误差校正。使用此观察,我们提出了Quest(量子误差校正基板),该架构将量子误差校正的任务委托给硬件。 Quest使用专用的可编程微编码引擎来连续重放与纠错相关的指令流。任务的指令带宽要求与活动Qubits数量(通常<; <; 0.1%)而不是Qubits总数的比例。我们分析了Quest与区域和热约束的有效性,并使用典型的量子误差校正码(QECC)执行模式提出可伸缩的微架构。我们的评估表明,Quest通过FTVE数量级降低了几个关键工作量的指令带宽需求,同时确保确定性指令传送。除了纠错外,还观察到容错量子指令的大指令带宽要求(魔术状态蒸馏)。我们扩展了在硬件中管理这些指令的追求,并提供带宽的额外减少。通过Quest,我们将总指令带宽降低了八个数量级。

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