409 results about "Computational problem" patented technology

A method of encoding knowledge is disclosed, which can be used to automatically detect problems in software application deployments. The method includes accessing a source of knowledge describing a problem known to occur in deployments of a particular software application, and which identifies a plurality of conditions associated with the problem. An encoded representation of the knowledge source is generated according to a predefined knowledge encoding methodology. The encoded representation is adapted to be applied automatically by a computer to analyze data representing a current state of a monitored deployment of the software application to detect whether the conditions and the problem exist therein. In various implementations, the encoded representation of the knowledge can include queries for deployment information, information concerning the relative importance of the conditions to a detection of the problem, and/or logical constructs for computing a confidence value in the existence of the problem and for determining whether to report the problem if some of the conditions are not true. The knowledge source can comprise a text document (such as a knowledge base article), a flowchart of a diagnostic troubleshooting method, and the like. Also disclosed are methods of at least partially automating the encoding process.

Analog processors for solving various computational problems are provided. Such analog processors comprise a plurality of quantum devices, arranged in a lattice, together with a plurality of coupling devices. The analog processors further comprise bias control systems each configured to apply a local effective bias on a corresponding quantum device. A set of coupling devices in the plurality of coupling devices is configured to couple nearest-neighbor quantum devices in the lattice. Another set of coupling devices is configured to couple next-nearest neighbor quantum devices. The analog processors further comprise a plurality of coupling control systems each configured to tune the coupling value of a corresponding coupling device in the plurality of coupling devices to a coupling. Such quantum processors further comprise a set of readout devices each configured to measure the information from a corresponding quantum device in the plurality of quantum devices.

A method for computing using a quantum system comprising a plurality of superconducting qubits is provided. Quantum system can be in any one of at least two configurations including (i) an initialization Hamiltonian H₀ and (ii) a problem Hamiltonian H_P. The plurality of superconducting qubits are arranged with respect to one another, with a predetermined number of couplings between respective pairs of superconducting qubits in the plurality of qubits, such that the plurality of superconducting qubits, coupled by the predetermined number of couplings, collectively define a computational problem to be solved. In the method, quantum system is initialized to the initialization Hamiltonian H_O. Quantum system is then adiabatically changed until it is described by the ground state of the problem Hamiltonian H_P. The quantum state of quantum system is then readout thereby solving the computational problem to be solved.

A method for quantum computing using a quantum system comprising a plurality of qubits is provided. The system can be in any one of at least two configurations at any given time including one characterized by an initialization Hamiltonian H₀ and one characterized by a problem Hamiltonian H_P. The problem Hamiltonian H_P has a final state. Each respective first qubit in the qubits is arranged with respect to a respective second qubit in the qubits such that they define a predetermined coupling strength. The predetermined coupling strengths between the qubits in the plurality of qubits collectively define a computational problem to be solved. In the method, the system is initialized to H₀ and is then adiabatically changed until the system is described by the final state of the problem Hamiltonian H_P. Then the state of the system is read out by probing an observable of the σ_X Pauli matrix operator.

A distributed parallel computing system actively takes advantage of problem partitioning to balance the computing load among computing resources continually during processing. Variable problem partitions (VPPs) are initially defined as groups of original problem cells (OPCs). VPPs may be redefined and redistributed during execution, if necessary, to optimize performance based on the actual computing agent parameters and costs observed or reported through self-tests. For example, a good rule for efficient execution of a computing problem may be that the time required to perform a computation sequence (iteration) of all OPCs in a VPP should be comparable to the time required to share results via edge OPCs at the VPP collection perimeters. The rules that yield cost-efficient execution may be saved and re-used to generate initial partitionings for subsequent computing problem execution runs.

Systems, devices, and methods for using an analog processor to solve computational problems. A digital processor is configured to track computational problem processing requests received from a plurality of different users, and to track at least one of a status and a processing cost for each of the computational problem processing requests. An analog processor, for example a quantum processor, is operable to assist in producing one or more solutions to computational problems identified by the computational problem processing requests via a physical evolution.

Determining semantically equivalent text or questions using hybrid representations based on neural network learning. Weighted bag-of-words and convolutional neural networks (CNN) based distributed vector representations of questions or text may be generated to compute the semantic similarity between questions or text. Weighted bag-of-words and CNN based distributed vector representations may be jointly used to compute the semantic similarity. A pair-wise ranking loss function trains neural network. In one embodiment, the parameters of the system are trained by minimizing a pair-wise ranking loss function over a training set using stochastic gradient descent (SGD).

Analog processors for solving various computational problems are provided. Such analog processors comprise a plurality of quantum devices, for instance qubits, arranged in a lattice, together with a plurality of coupling devices. The analog processors further comprise bias control systems each configured to apply a local effective bias on a corresponding quantum device. A set of coupling devices in the plurality of coupling devices is configured to couple nearest-neighbor quantum devices in the lattice. Another set of coupling devices is configured to couple next-nearest neighbor quantum devices. The analog processors further comprise a plurality of coupling control systems each configured to tune the coupling value of a corresponding coupling device in the plurality of coupling devices to a coupling. Such quantum processors further comprise a set of readout devices each configured to measure the information from a corresponding quantum device in the plurality of quantum devices.

Quantum and digital processors are employed together to solve computational problems. The quantum processor may be configured with a problem via a problem Hamiltonian and operated to perform adiabatic quantum computation and/or quantum annealing on the problem Hamiltonian to return a first solution to the problem that is in the neighborhood of the global minimum of the problem Hamiltonian. The digital processor may then be used to refine the first solution to the problem by casting the first solution to the problem as a starting point for a classical optimization algorithm. The classical optimization algorithm may return a second solution to the problem that corresponds to a lower energy state in the neighborhood of the global minimum, such as a ground state of the problem Hamiltonian. The quantum processor may include a superconducting quantum processor implementing superconducting flux qubits.

A benefit task system implements a policy for allocating resources to yield some benefit. The method implemented may be applied to a variety of problems, and the benefit may be either tangible (e.g., profit) or intangible (e.g., customer satisfaction). In one example, the method is applied to server allocation in a Web site server "farm" given full information regarding future loads to maximize profits for the Web hosting service provider. In another example, the method is applied to the allocation of telephone help in a way to improve customer satisfaction. In yet another example, the method is applied to distributed computing problem where the resources to be allocated are general purpose computers connected in a network and used to solve computationally intensive problems. Solution of the Web server "farm" problem is based on information regarding future loads to achieve close to the greatest possible revenue based on the assumption that revenue is proportional to the utilization of servers and differentiated by customer class. The method of server allocation uses an approach which reduces the Web server farm problem to a minimum-cost network flow problem, which can be solved in polynomial time. Similar solutions are applicable to other resource allocation problems.

Optimal Decision Feedback Equalizer (DFE) coefficients are determined from a channel estimate by casting the DFE coefficient problem as a standard recursive least squares (RLS) problem and solving the RLS problem. In one embodiment, a fast recursive method, e.g., fast transversal filter (FTF) technique, is used to compute the Kalman gain of the RLS problem, which is then directly used to compute MIMO Feed Forward Equalizer (FFE) coefficients. The FBE coefficients are computed by convolving the FFE coefficients with the channel impulse response. Complexity of a conventional FTF algorithm may be reduced to one third of its original complexity by selecting a DFE delay to force the FTF algorithm to use a lower triangular matrix. The length of the DFE may be selected to minimize the tap energy in the FBE coefficients or to ensure that the tap energy in the FBE coefficients meets a threshold.

The invention provides a distributed system node processing task managing method which includes the steps of receiving an external task request, storing a task in a task buffer of a management node, when some computational node is connected and asks for the task, sending the task to the computational node, and receiving task results when the task processing results are sent by the computational node. By means of the distributed system node processing task method, automation of the whole task processing process is achieved through simple configuration, the management cost is reduced, and in-time finding and in-time processing on the computational node with faults are facilitated.

This invention discloses a carrying guidance system in the route optimum domain, which comprises the following steps: establishing a biparametric path unit standard dynamic file; considering the path rational constrained and joint failure constrained; using the method of heuristics weight to establish the optional path set off line; improving A* heuristics function to increase the efficiency of optional path set which satisfies the customer rational constrained and joint failure constrained; Off-line optional path set coded storing and backtrack on line; screening of on-line dynamic path, supplementary searching and multiple path issue.

Producing multiple independent fields from many phased acoustic transducers represents a difficult computational problem. By first dividing up each field to its own group of transducers and then treating each group as an element with adjustable phase, one can minimize the field-to-field interference through a power iteration solution. These solutions can be further refined by including tracking information from users in the space and how they shadow or reflect the acoustic fields.