تقرير
mpiQulacs: A Distributed Quantum Computer Simulator for A64FX-based Cluster Systems
| العنوان: | mpiQulacs: A Distributed Quantum Computer Simulator for A64FX-based Cluster Systems |
|---|---|
| المؤلفون: | Imamura, Satoshi, Yamazaki, Masafumi, Honda, Takumi, Kasagi, Akihiko, Tabuchi, Akihiro, Nakao, Hiroshi, Fukumoto, Naoto, Nakashima, Kohta |
| سنة النشر: | 2022 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Distributed, Parallel, and Cluster Computing |
| الوصف: | Quantum computer simulators running on classical computers are essential for developing real quantum computers and emerging quantum applications. In particular, state vector simulators, which store a full state vector in memory and update it in every quantum operation, are available to simulate an arbitrary form of quantum circuits, debug quantum applications, and validate future quantum computers. However, the time and space complexity grows exponentially with the number of qubits and easily exceeds the capability of a single machine. Therefore, we develop a distributed state vector simulator, $mpiQulacs$, that is optimized for large-scale simulation on A64FX-based cluster systems. A64FX is an ARM-based CPU that is also equipped in the world's top Fugaku supercomputer. We evaluate weak and strong scaling of mpiQulacs with up to 36 qubits on a new 64-node A64FX-based cluster system named $Todoroki$. By comparing mpiQulacs with existing distributed state vector simulators, we show that mpiQulacs achieves the highest performance for large-scale simulation on tens of nodes while sustaining a nearly ideal scalability. Besides, we define a new metric, $quantum B/F ratio$, and use it to demonstrate that mpiQulacs running on Todoroki fits the requirements of distributed state vector simulation rather than the existing simulators running on general purpose CPU-based or GPU-based cluster systems. Comment: This preprint is related to the press release of Fujitsu LTD. in https://www.fujitsu.com/global/about/resources/news/press-releases/2022/0330-01.html, 11 pages, 12 figures |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2203.16044 |
| رقم الأكسشن: | edsarx.2203.16044 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |