We present Qibo, a new open-source software for fast evaluation of quantum circuits and adiabatic evolution which takes full advantage of hardware accelerators. The growing interest in quantum computing and the recent developments of quantum hardware devices motivates the development of new advanced computational tools focused on performance and usage simplicity. In this work we introduce a new quantum simulation framework that enables developers to delegate all complicated aspects of hardware or platform implementation to the library so they can focus on the problem and quantum algorithms at hand. This software is designed from scratch with simulation performance, code simplicity and user friendly interface as target goals. It takes advantage of hardware acceleration such as multi-threading Central Processing Unit (CPU), single Graphics Processing Unit (GPU) and multi-GPU devices.

Qibo: a framework for quantum simulation with hardware acceleration / S. Efthymiou, S. Ramos-Calderer, C. Bravo-Prieto, A. Pérez-Salinas, D. García-Martín, A. Garcia-Saez, J. Ignacio Latorre, S. Carrazza. - In: QUANTUM SCIENCE AND TECHNOLOGY. - ISSN 2058-9565. - 7:(2022), pp. 015018.1-015018.19. [10.1088/2058-9565/ac39f5]

Qibo: a framework for quantum simulation with hardware acceleration

S. Carrazza
Ultimo
2022

Abstract

We present Qibo, a new open-source software for fast evaluation of quantum circuits and adiabatic evolution which takes full advantage of hardware accelerators. The growing interest in quantum computing and the recent developments of quantum hardware devices motivates the development of new advanced computational tools focused on performance and usage simplicity. In this work we introduce a new quantum simulation framework that enables developers to delegate all complicated aspects of hardware or platform implementation to the library so they can focus on the problem and quantum algorithms at hand. This software is designed from scratch with simulation performance, code simplicity and user friendly interface as target goals. It takes advantage of hardware acceleration such as multi-threading Central Processing Unit (CPU), single Graphics Processing Unit (GPU) and multi-GPU devices.
Quantum Physics; Quantum Physics; Computer Science - Distributed; Parallel; and Cluster Computing; Computer Science - Learning
Settore FIS/02 - Fisica Teorica, Modelli e Metodi Matematici
2022
16-dic-2021
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/887963
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