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公开(公告)号:US11481469B2
公开(公告)日:2022-10-25
申请号:US14854839
申请日:2015-09-15
Applicant: QUALCOMM TECHNOLOGIES, INC.
Inventor: James Ezick , Thomas Henretty , Chanseok Oh , Jonathan Springer
Abstract: We present the architecture of a high-performance constraint solver R-Solve that extends the gains made in SAT performance over the past fifteen years on static decision problems to problems that require on-the-fly adaptation, solution space exploration and optimization. R-Solve facilitates collaborative parallel solving and provides an efficient system for unrestricted incremental solving via Smart Repair. R-Solve can address problems in dynamic planning and constrained optimization involving complex logical and arithmetic constraints.
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公开(公告)号:US11797894B1
公开(公告)日:2023-10-24
申请号:US17098916
申请日:2020-11-16
Applicant: QUALCOMM TECHNOLOGIES, INC
Inventor: James Ezick , Jonathan Springer , Nicolas T. Vasilache
Abstract: In a system for enabling configuration of an ensemble of several solvers, such that the ensemble can efficiently solve a constraint problem, for each one of several candidate configurations, an array of scores is computed. The array corresponds to a statistical parameter related to a problem solution, and the computation is based on, at least in part, a set of features associated with the problem. One candidate configuration is assigned to a solver, and based on the array of scores associated with that candidate configuration the same or a different candidate configuration is assigned to a another solver. A system for dynamically reconfiguring an ensemble of solvers obtains runtime data from several solvers, and a new configuration is determined by applying a machine learning and/or heuristic analysis procedure to the runtime data. The configuration of a solver may be updated according to the new configuration while that solver is running.
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公开(公告)号:US11481468B2
公开(公告)日:2022-10-25
申请号:US14729731
申请日:2015-06-03
Applicant: QUALCOMM TECHNOLOGIES, INC.
Inventor: James Ezick , Thomas Henretty , Chanseok Oh , Jonathan Springer
Abstract: We present the architecture of a high-performance constraint solver R-Solve that extends the gains made in SAT performance over the past fifteen years on static decision problems to problems that require on-the-fly adaptation, solution space exploration and optimization. R-Solve facilitates collaborative parallel solving and provides an efficient system for unrestricted incremental solving via Smart Repair. R-Solve can address problems in dynamic planning and constrained optimization involving complex logical and arithmetic constraints.
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