Performance Models for Split-Execution Computing Systems
Performance Models for Split-Execution Computing Systems
复制标题
分割执行计算系统的性能模型
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
N. Imam
中科院分区：
文献类型：
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作者：
T. Humble;A. McCaskey;Jonathan Schrock;H. Seddiqi;Keith A. Britt;N. Imam
分割执行计算利用多个计算模型的能力来解决问题，但跨不同计算模型分割程序执行会导致与域之间的转换相关的成本。通过使用跟踪资源使用情况的行为模型，我们分析了由传统处理单元和量子处理单元(QPU)发展而来的分割执行计算系统的性能。我们专注于使用传统CPU和一系列采用量子计算原理的特殊用途QPU构建的非对称处理模型。我们的性能模型考虑了将经典优化问题转换为量子处理器所需的物理表示，同时也考虑了硬件限制和传统的处理器速度和内存。我们得出的结论是，这种分裂执行计算系统的瓶颈在于量子经典界面，并且主要的时间开销与量子处理器的行为无关。
Split-execution computing leverages the capabilities of multiple computational models to solve problems, but splitting program execution across different computational models incurs costs associated with the translation between domains. We analyze the performance of a split-execution computing system developed from conventional and quantum processing units (QPUs) by using behavioral models that track resource usage. We focus on asymmetric processing models built using conventional CPUs and a family of special-purpose QPUs that employ quantum computing principles. Our performance models account for the translation of a classical optimization problem into the physical representation required by the quantum processor while also accounting for hardware limitations and conventional processor speed and memory. We conclude that the bottleneck in this split-execution computing system lies at the quantum-classical interface and that the primary time cost is independent of quantum processor behavior.