LSQCA: Resource-Efficient Load/Store Architecture for Limited-Scale Fault-Tolerant Quantum Computing (2412.20486v2)

Abstract: Current fault-tolerant quantum computer (FTQC) architectures utilize several encoding techniques to enable reliable logical operations with restricted qubit connectivity. However, such logical operations demand additional memory overhead to ensure fault tolerance. Since the main obstacle to practical quantum computing is the limited qubit count, our primary mission is to design floorplans that can reduce memory overhead without compromising computational capability. Despite extensive efforts to explore FTQC architectures, even the current state-of-the-art floorplan strategy devotes 50% of memory space to this overhead, not to data storage, to ensure unit-time random access to all logical qubits. In this paper, we propose an FTQC architecture based on a novel floorplan strategy, Load/Store Quantum Computer Architecture (LSQCA), which can achieve almost 100% memory density. The idea behind our architecture is to separate all memory regions into small computational space called Computational Registers (CR) and space-efficient memory space called Scan-Access Memory (SAM). We define an instruction set for these abstract structures and provide concrete designs named point-SAM and line-SAM architectures. With this design, we can improve the memory density by allowing variable-latency memory access while concealing the latency with other bottlenecks. We also propose optimization techniques to exploit properties of quantum programs observed in our static analysis, such as access locality in memory reference timestamps. Our numerical results indicate that LSQCA successfully leverages this idea. In a resource-restricted situation, a specific benchmark shows that we can achieve about 90% memory density with 5% increase in the execution time compared to a conventional floorplan, which achieves at most 50% memory density for unit-time random access. Our design ensures broad quantum applicability.

• The paper introduces LSQCA, a novel Load/Store Quantum Computer Architecture that achieves high memory density in fault-tolerant quantum computing by separating computational registers from dense scan-access memory.
• LSQCA comprises Scan-Access Memory (SAM), Computational Registers (CR), and Magic State Factories (MSF), using Point-SAM or Line-SAM designs to optimize density and access latency.
• Empirical evaluation shows LSQCA provides superior memory density for quantum programs like SELECT circuits compared to conventional designs, with only modest increases in execution time.

LSQCA: Resource-Efficient Load/Store Architecture for Limited-Scale Fault-Tolerant Quantum Computing

The paper "LSQCA: Resource-Efficient Load/Store Architecture for Limited-Scale Fault-Tolerant Quantum Computing" introduces a novel architecture aimed at optimizing memory utilization in fault-tolerant quantum computers (FTQC). The proposed Load/Store Quantum Computer Architecture (LSQCA) significantly enhances memory density while maintaining computational capacity, addressing core challenges such as limited qubit counts and high-error rates inherent in FTQCs.

Context and Motivation

The need for FTQCs arises from their potential to solve specific problems more efficiently than classical computers, despite challenges including high error rates and limited qubit counts. Surface codes have become a promising method for quantum error correction (QEC) due to their implementability with nearest-neighbor interactions on two-dimensional grids. However, such implementations demand a considerable amount of auxiliary memory space beyond data storage to ensure fault-tolerant logical operations, traditionally consuming approximately 50% of total memory.

The paper proposes the LSQCA as an innovative architecture capable of almost 100% memory density by separating memory space into computational registers (CR) and Scan-Access Memory (SAM). This division allows the LSQCA to surpass the constraints of traditional FTQC designs by supporting variable-latency memory access efficiently.

Architecture and Design

LSQCA consists of three primary components:

1. Scan-Access Memory (SAM): Divided into sub-regions for high-density memory storage with a small allocation of auxiliary cells for loading and storing operations.
2. Computational Registers (CR): A small but dedicated space for executing logical operations immediately upon data transfer.
3. Magic State Factories (MSF): Specialized regions for producing magic states essential for certain quantum operations, ensuring efficient state preparation.

The key innovation is in the SAM design, categorized into two architectures:

• Point-SAM: Focuses on maximizing memory efficiency with minimal auxiliary cell usage.
• Line-SAM: Extends auxiliary cell utilization for improved access latency by optimizing logical qubit operations along a scan line.

Instruction Set and Operations

The LSQCA introduces a comprehensive instruction set tailored for quantum computing, featuring variable-latency load (LD) and store (ST) operations that allow logical qubits to be moved between SAM and CR. This set also includes standard preparation, unitary, and measurement operations, as well as in-memory operations that exploit the spatial and temporal locality of logical qubit accesses observed in quantum programs.

Empirical Evaluation

The architecture's performance was evaluated using realistic quantum programs such as SELECT circuits and multiplication circuits. Numerical results demonstrate that LSQCA achieves superior memory density relative to conventional floorplans, which is particularly valuable in resource-constrained scenarios. For instance, under a limited-resource setup, the LSQCA achieved approximately 90% memory density for SELECT and multiplication benchmarks with only a modest increase in execution time.

Implications and Future Work

The conceptual separation of computational and memory spaces within the LSQCA framework introduces a versatile approach to resource management in quantum computing, potentially applicable across diverse quantum devices, connectivity topologies, and error-correcting configurations. The architecture aligns with the growing demand for efficient load/store strategies as it balances flexibility and performance.

Future research directions include refining instruction scheduling to further mask memory-access latency and exploring adaptive techniques for data allocation and prefetching based on dynamic access pattern analysis. These enhancements could lead to further reductions in execution overhead, cementing LSQCA's utility in achieving efficient, large-scale fault-tolerant quantum computing.

In summary, the LSQCA marks a significant shift toward higher memory density and computational efficiency in quantum architectures, paving the way for scalable and practical quantum computing solutions.