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公开(公告)号:US11520856B2
公开(公告)日:2022-12-06
申请号:US17086772
申请日:2020-11-02
Applicant: QUALCOMM TECHNOLOGIES, INC.
Inventor: Muthu M. Baskaran , David Bruns-Smith , James Ezick , Richard A. Lethin
IPC: G06F17/16
Abstract: A system for performing tensor decomposition in a selective expansive and/or recursive manner, a tensor is decomposed into a specified number of components, and one or more tensor components are selected for further decomposition. For each selected component, the significant elements thereof are identified, and using the indices of the significant elements a sub-tensor is formed. In a subsequent iteration, each sub-tensor is decomposed into a respective specified number of components. Additional sub-tensors corresponding to the components generated in the subsequent iteration are formed, and these additional sub-tensors may be decomposed further in yet another iteration, until no additional components are selected. The mode of a sub-tensor can be decreased or increased prior to decomposition thereof. Components likely to reveal information about the data stored in the tensor can be selected for decomposition.
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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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