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Title: Performance Models for Split-execution Computing Systems

Abstract

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.

Authors:
 [1];  [1];  [1];  [1];  [1];  [1]
  1. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1302895
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: 18th Workshop on Advances in Parallel and Distributed Computational Models, Chicago, IL, USA, 20160302, 20160302
Country of Publication:
United States
Language:
English
Subject:
quantum computing; split-execution; multiprocessor

Citation Formats

Humble, Travis S, McCaskey, Alex, Schrock, Jonathan, Seddiqi, Hadayat, Britt, Keith A, and Imam, Neena. Performance Models for Split-execution Computing Systems. United States: N. p., 2016. Web. doi:10.1109/IPDPSW.2016.113.
Humble, Travis S, McCaskey, Alex, Schrock, Jonathan, Seddiqi, Hadayat, Britt, Keith A, & Imam, Neena. Performance Models for Split-execution Computing Systems. United States. doi:10.1109/IPDPSW.2016.113.
Humble, Travis S, McCaskey, Alex, Schrock, Jonathan, Seddiqi, Hadayat, Britt, Keith A, and Imam, Neena. Fri . "Performance Models for Split-execution Computing Systems". United States. doi:10.1109/IPDPSW.2016.113.
@article{osti_1302895,
title = {Performance Models for Split-execution Computing Systems},
author = {Humble, Travis S and McCaskey, Alex and Schrock, Jonathan and Seddiqi, Hadayat and Britt, Keith A and Imam, Neena},
abstractNote = {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.},
doi = {10.1109/IPDPSW.2016.113},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2016},
month = {1}
}

Conference:
Other availability
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