一种整合量子模拟与高性能计算的框架
A Framework for Integrating Quantum Simulation and High Performance Computing
AI总结：
针对HPC上量子模拟软件配置使用门槛高的问题，提出含任务接口与资源管理的整合框架，分类使用模式、阐述架构并给出双模拟器原型，还在Frontier超算上完成了初步基准测试。
摘要：
科学应用正开始探索量子计算的可行性。这类探索通常从可在现有经典平台上运行的量子模拟起步，尽管这类模拟无法发挥真实量子资源的性能优势。在高性能计算（HPC）语境下，引入模拟软件通常可利用其强大资源来扩大模拟规模。但在HPC资源上配置、安装和运行这些量子模拟软件包往往相当复杂，会增加科学应用开发者开展实验的阻碍。我们提出了一个框架，旨在简化对运行在HPC资源上的量子模拟软件的访问流程。该框架包含一个面向基于线路的量子计算任务的接口，以及用于有效利用底层HPC资源的必要资源管理基础设施。本工作的主要贡献包括：对HPC环境下量子模拟的不同使用模式进行分类，阐述我们所提方法的软件架构，并详细介绍使用两种不同模拟器（TNQVM与NWQ-Sim）验证这些思路的原型实现。我们还给出了在橡树岭领导力计算设施（OLCF）的Frontier超级计算机上，利用SupermarQ量子基准测试框架生成的合成工作负载运行得到的初步实验结果。
英文摘要：
Scientific applications are starting to explore the viability of quantum computing. This exploration typically begins with quantum simulations that can run on existing classical platforms, albeit without the performance advantages of real quantum resources. In the context of high-performance computing (HPC), the incorporation of simulation software can often take advantage of the powerful resources to help scale-up the simulation size. The configuration, installation and operation of these quantum simulation packages on HPC resources can often be rather daunting and increases friction for experimentation by scientific application developers. We describe a framework to help streamline access to quantum simulation software running on HPC resources. This includes an interface for circuit-based quantum computing tasks, as well as the necessary resource management infrastructure to make effective use of the underlying HPC resources. The primary contributions of this work include a classification of different usage models for quantum simulation in an HPC context, a review of the software architecture for our approach and a detailed description of the prototype implementation to experiment with these ideas using two different simulators (TNQVM \& NWQ-Sim). We include initial experimental results running on the Frontier supercomputer at the Oak Ridge Leadership Computing Facility (OLCF) using a synthetic workload generated via the SupermarQ quantum benchmarking framework.
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