Practical applications of quantum computers require millions of physical qubits and it will be challenging for individual quantum processors to reach such qubit numbers. It is therefore timely to investigate the resource requirements of quantum algorithms in a distributed setting, where multiple quantum processors are interconnected by a coherent network. We introduce an extension of the Message Passing Interface (MPI) to enable high-performance implementations of distributed quantum algorithms. In turn, these implementations can be used for testing, debugging, and resource estimation. In addition to a prototype implementation of quantum MPI, we present a performance model for distributed quantum computing, SENDQ. The model is inspired by the classical LogP model, making it useful to inform algorithmic decisions when programming distributed quantum computers. Specifically, we consider several optimizations of two quantum algorithms for problems in physics and chemistry, and we detail their effects on performance in the SENDQ model.
翻译:量子计算机的实际应用需要数以百万计的物理当量位数,这对单个量子处理器达到这种当量子数数数数字具有挑战性。 因此,在分布式环境中调查量子算法的资源需求是及时的,在分布式环境中,多个量子处理器通过一个连贯的网络相互连接。 我们引入了信息传递接口(MPI)的扩展,以便高性能地实施分布量子算法。反过来,这些应用可用于测试、调试和资源估算。 除了量子 MPI的原型实施外,我们还提出了一个分布式量子计算性能模型,SENDQ。该模型受经典的Lopp模型的启发,在编程量子计算机时有助于为算法决定提供信息。具体地说,我们考虑对物理和化学问题的两种量子算法进行若干优化,我们在SENDQ模型中详细说明其对性能的影响。