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Mera: Memory Reduction and Acceleration for Quantum Circuit Simulation via Redundancy Exploration | IEEE Conference Publication | IEEE Xplore

Mera: Memory Reduction and Acceleration for Quantum Circuit Simulation via Redundancy Exploration


Abstract:

With the development of quantum computing, quantum processor demonstrates the potential supremacy in specific applications, such as Grover's database search and popular q...Show More

Abstract:

With the development of quantum computing, quantum processor demonstrates the potential supremacy in specific applications, such as Grover's database search and popular quantum neural networks (QNNs). For better calibrating the quantum algorithms and machines, quantum circuit simulation on classical computers becomes crucial. However, as the number of quantum bits (qubits) increases, the memory requirement grows exponentially. In order to reduce memory usage and accelerate simulation, we propose a multi-level optimization, namely Mera, by exploring memory and computation redundancy. First, for a large number of sparse quantum gates, we propose two compressed structures for low-level full-state simulation. The corresponding gate operations are designed for practical implementations, which are relieved from the longtime compression and decompression. Second, for the dense Hadamard gate, which is definitely used to construct the superposition, we design a customized structure for significant memory saving as a regularity-oriented simulation. Meanwhile, an ondemand amplitude updating process is optimized for execution acceleration. Experiments show that our compressed structures increase the number of qubits from 17 to 35, and achieve up to 6.9 \times acceleration for QNN.
Date of Conference: 18-20 November 2024
Date Added to IEEE Xplore: 02 January 2025
ISBN Information:

ISSN Information:

Conference Location: Milan, Italy

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I. Introduction

Noisy intermediate-scale quantum (NISQ) machines have been proved their quantum supremacy [1]. Benefiting from the superposition and entanglement of quantum bit (qubit), quantum computers demonstrate huge advantages over classical computers in some specific applications, like Shor's integer factorization [2], Grover's database search [3], and quantum neural networks (QNNs) [4], [5]. Because of the immaturity and huge overhead of existing physical quantum processors, simulation on classical computers becomes crucial for better understanding quantum behaviors. Among different types of quantum simulators [6], full-state simulation [7] becomes important, because it allows deeper and larger quantum circuit simulation. It updates the state-vector in each time step.

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