Parallelization of the QC-Lib Quantum Computer Simulator Library

Glendinning, I.; Ömer, Bernhard

doi:10.1007/978-3-540-24669-5_60

Cited by 12 publications

(12 citation statements)

References 3 publications

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“…It is obvious that the simulation of quantum problems of interesting sizes enforces the use of high performance computing devices. Parallel computing can represent a solution to this problem [5,7,10,13].…”

Section: Parallel Simulation Of Quantum Computationmentioning

confidence: 99%

Parallel Simulation of Quantum Search

Caraiman

Manta

2010

INT J COMPUT COMMUN

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Simulation of quantum computers using classical computers is a computationally hard problem, requiring a huge amount of operations and storage. Parallelization can alleviate this problem, allowing the simulation of more qubits at the same time or the same number of qubits to be simulated in less time. A promising approach is represented by executing these simulators in Grid systems that can provide access to high performance resources. In this paper we present a parallel implementation of the QC-lib quantum computer simulator deployed as a Grid service. Using a specific scheme for partitioning the terms describing quantum states and efficient parallelization of the general singe qubit operator and of the controlled operators, very good speed-ups were obtained for the simulation of the quantum search problem.

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Section: Parallel Simulation Of Quantum Computationmentioning

confidence: 99%

Parallel Simulation of Quantum Search

Caraiman

Manta

2010

INT J COMPUT COMMUN

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“…On the one hand, existing technology allows only to construct quantum computers of very reduced dimensions [7], and on the other hand, only a small number of effective algorithms [5,8,13] are known. Nevertheless, the analysis of this computational model constitutes a topic of great interest for physicists, computer scientists and engineers.…”

Section: Introductionmentioning

confidence: 99%

“…Nevertheless, the analysis of this computational model constitutes a topic of great interest for physicists, computer scientists and engineers. Actually, a quantum computer can be considered as a hardware accelerator of the classical processor, from which it receives the orders for the resolution of a concrete problem [7], as shown in Fig. 1.…”

Section: Introductionmentioning

confidence: 99%

“…This causes quantum computer simulation to demand high computational power. This way, parallelism is a suitable tool for mitigating such requirements [7,11]. The simulation of quantum computers not only requires a high computational effort but they present data access patterns with low locality characteristics.…”

Section: Introductionmentioning

confidence: 99%

“…The simulation of quantum computers not only requires a high computational effort but they present data access patterns with low locality characteristics. Several interests arise for this kind of simulation giving raise to the development of different simulators, both in software [2,3,7,11] as in hardware [6,9,14].…”

Section: Introductionmentioning

confidence: 99%

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Parallel Quantum Computer Simulation on the CUDA Architecture

Gutiérrez

Romero

Trenas

et al. 2008

Computational Science – ICCS 2008

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Abstract. Due to their increasing computational power, modern graphics processing architectures are becoming more and more popular for general purpose applications with high performance demands. This is the case of quantum computer simulation, a problem with high computational requirements both in memory and processing power. When dealing with such simulations, multiprocessor architectures are an almost obliged tool. In this paper we explore the use of the new graphics processor architecture NVIDIA CUDA in the simulation of some basic quantum computing operations. This new architecture is oriented towards a more general exploitation of the graphics platform, allowing to use it as a parallel SIMD multiprocessor. In this direction, some implementation strategies are proposed, showing that the effectiveness of the codes is subject to a right exploitation of the underlying memory hierarchy.

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Quantum computing: A taxonomy, systematic review and future directions

et al. 2021

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Quantum computing (QC) is an emerging paradigm with the potential to offer significant computational advantage over conventional classical computing by exploiting quantum‐mechanical principles such as entanglement and superposition. It is anticipated that this computational advantage of QC will help to solve many complex and computationally intractable problems in several application domains such as drug design, data science, clean energy, finance, industrial chemical development, secure communications, and quantum chemistry. In recent years, tremendous progress in both quantum hardware development and quantum software/algorithm has brought QC much closer to reality. Indeed, the demonstration of quantum supremacy marks a significant milestone in the Noisy Intermediate Scale Quantum (NISQ) era—the next logical step being the quantum advantage whereby quantum computers solve a real‐world problem much more efficiently than classical computing. As the quantum devices are expected to steadily scale up in the next few years, quantum decoherence and qubit interconnectivity are two of the major challenges to achieve quantum advantage in the NISQ era. QC is a highly topical and fast‐moving field of research with significant ongoing progress in all facets. A systematic review of the existing literature on QC will be invaluable to understand the state‐of‐the‐art of this emerging field and identify open challenges for the QC community to address in the coming years. This article presents a comprehensive review of QC literature and proposes taxonomy of QC. The proposed taxonomy is used to map various related studies to identify the research gaps. A detailed overview of quantum software tools and technologies, post‐quantum cryptography, and quantum computer hardware development captures the current state‐of‐the‐art in the respective areas. The article identifies and highlights various open challenges and promising future directions for research and innovation in QC.

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Parallelization of the QC-Lib Quantum Computer Simulator Library

Cited by 12 publications

References 3 publications

Parallel Simulation of Quantum Search

Parallel Simulation of Quantum Search

Parallel Quantum Computer Simulation on the CUDA Architecture

Quantum computing: A taxonomy, systematic review and future directions

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