量子反计算的程序转换与体系结构支持

ASPLOS XII Pub Date : 2006-10-23 DOI:10.1145/1168857.1168889
E. Schuchman, T. N. Vijaykumar
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引用次数: 8

摘要

量子计算的能力来自于利用量子力学现象进行计算的新算法。量子算法与经典算法的不同之处在于,量子算法依赖于经典计算中根本不存在的算法结构。正如经典程序转换和体系结构是为常见的经典算法结构设计的一样,量子程序转换和量子体系结构应该在设计时考虑到量子算法。由于量子算法与这些新的算法结构一起出现,由此产生的量子程序转换和架构可能看起来与它们的经典对应物非常不同。本文重点研究了量子算法中一个关键且普遍的结构——非计算,并考虑了如何设计程序转换和架构支持来适应非计算。在本文中,我们展示了一个简单的量子程序转换,它揭示了未计算和后期计算之间的独立性。然后,我们提出了针对这种暴露的并行性量身定制的多核体系结构,并提出了将这种并行性有效地映射到多核体系结构的调度策略。我们的策略在减少累计通信距离的同时实现了未计算和后期计算的并行性。我们的调度和架构允许量子程序的显著加速(在Shor的分解算法中加速1.8到2.8倍),同时减少26%的累积通信距离。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A program transformation and architecture support for quantum uncomputation
Quantum computing's power comes from new algorithms that exploit quantum mechanical phenomena for computation. Quantum algorithms are different from their classical counterparts in that quantum algorithms rely on algorithmic structures that are simply not present in classical computing. Just as classical program transformations and architectures have been designed for common classical algorithm structures, quantum program transformations and quantum architectures should be designed with quantum algorithms in mind. Because quantum algorithms come with these new algorithmic structures, resultant quantum program transformations and architectures may look very different from their classical counterparts.This paper focuses on uncomputation, a critical and prevalent structure in quantum algorithms, and considers how program transformations, and architecture support should be designed to accommodate uncomputation. In this paper,we show a simple quantum program transformation that exposes independence between uncomputation and later computation. We then propose a multicore architecture tailored to this exposed parallelism and propose a scheduling policy that efficiently maps such parallelism to the multicore architecture. Our policy achieves parallelism between uncomputation and later computation while reducing cumulative communication distance. Our scheduling and architecture allows significant speedup of quantum programs (between 1.8x and 2.8x speedup in Shor's factoring algorithm), while reducing cumulative communication distance 26%.
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