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Resource-Efficient Quantum Computing by Breaking Abstractions
Proceedings of the IEEE ( IF 20.6 ) Pub Date : 2020-08-01 , DOI: 10.1109/jproc.2020.2994765
Yunong Shi , Pranav Gokhale , Prakash Murali , Jonathan M. Baker , Casey Duckering , Yongshan Ding , Natalie C. Brown , Christopher Chamberland , Ali Javadi-Abhari , Andrew W. Cross , David I. Schuster , Kenneth R. Brown , Margaret Martonosi , Frederic T. Chong

Building a quantum computer that surpasses the computational power of its classical counterpart is a great engineering challenge. Quantum software optimizations can provide an accelerated pathway to the first generation of quantum computing (QC) applications that might save years of engineering effort. Current quantum software stacks follow a layered approach similar to the stack of classical computers, which was designed to manage the complexity. In this review, we point out that greater efficiency of QC systems can be achieved by breaking the abstractions between these layers. We review several works along this line, including two hardware-aware compilation optimizations that break the quantum instruction set architecture (ISA) abstraction and two error-correction/information-processing schemes that break the qubit abstraction. Last, we discuss several possible future directions.

中文翻译:

通过打破抽象实现资源高效的量子计算

建造一台超越经典计算机计算能力的量子计算机是一项巨大的工程挑战。量子软件优化可以加速实现第一代量子计算 (QC) 应用程序,从而节省数年的工程工作量。当前的量子软件堆栈遵循类似于经典计算机堆栈的分层方法,旨在管理复杂性。在这篇评论中,我们指出通过打破这些层之间的抽象可以实现更高的 QC 系统效率。我们回顾了这方面的几项工作,包括两个打破量子指令集架构 (ISA) 抽象的硬件感知编译优化和两个打破量子位抽象的纠错/信息处理方案。最后的,
更新日期:2020-08-01
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