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Quantum computing promises an effective way to solve targeted problems that are classically intractable. Among them, quantum computers built with superconducting qubits are considered one of the most advanced technologies, but they suffer from short coherence times. This can get exaggerated when they are controlled directly by general-purpose host machines, which in turn leads to the loss of quantum information. To mitigate this, we need quantum control processors (QCPs) positioned between quantum processing units (QPUs) and host machines to reduce latencies. However, existing QCPs are built on top of designs with no or inefficient scalability, requiring a large number of instructions when scaling to more qubits. In addition, interactions between current QCPs and host machines require frequent data transmissions and offline computations to obtain final results from hundreds of repeated executions, which limits the performance of quantum computers.In this paper, we propose a QCP &#x2014; called HiSEP-Q &#x2014; featuring a novel quantum instruction set architecture (QISA) and its microarchitecture implementation. For efficient control, we utilize mixed-type addressing modes and mixed-length instructions in HiSEP-Q, which provides an efficient way to concurrently address more than 100 qubits. Further, for efficient read-out and analysis, we develop a novel onboard accumulation and sorting unit, which eliminates the data transmission of raw data between the QCPs and host machines and enables real-time result processing. Compared to the state-of-the-art, our proposed QISA achieves at least 62% and 28% improvements in encoding efficiency with real and synthetic quantum circuits, respectively. We also validate the microarchitecture on a field-programmable gate array (FPGA), which exhibits low power and resource consumption, even as the number of qubits scales to 100. Both hardware and ISA evaluations demonstrate that HiSEP-Q features high scalability and efficiency toward the number of controlled qubits.

HiSEP-Q: A Highly Scalable and Efficient Quantum Control Processor for Superconducting Qubits