Abstract: A method is disclosed to simulate operation of a grid structure. The method includes specifying a type of simulation to be performed and at least one initial condition with a user interface of a device such as a mobile device, where the grid structure comprises at least one of a power generation grid and a power distribution grid. The method further includes transmitting the specified type of simulation and the at least one initial condition from the user device to a computing platform; receiving from the computing platform a result of the simulation at the user device; and visualizing the result of the simulation with the user interface. The type of simulation can be an N-k contingency analysis simulation, where k is equal to zero, 1 or greater than 1.

Abstract: The present application relates to systems for generating new variants from an existing corpus of documents and methods for using the same. The systems and methods generally comprise a corpus of documents and one or more types of variety provided by a user. The system generates one or more documents that are variants of the documents in the corpus of documents.

Abstract: A data processing system includes a user interface with a user input configured to enable a user to specify a type of simulation to be performed and at least one initial condition, where the simulation is executed using at least one sensor input from a grid structure composed of at least one of a power transmission and distribution grid. The user interface further has a display configured to visualize a representation of a result of a simulation of at least one scenario by presenting a multi-dimensional representation comprised of indicators, where each indicator corresponds to at least one simulation result. The user interface responds to a selection of one of the indicators by the user to visualize a result of the corresponding simulation. The type of simulation can be an N?k contingency analysis simulation, where k is equal to zero, 1 or greater than 1.

Abstract: An array of resistive processing units (RPUs) comprises a plurality of rows of RPUs and a plurality of columns of RPUs wherein each RPU comprises an AND gate configured to perform an AND operation of a first stochastic bit stream received from a first stochastic translator translating a number encoded from a neuron in a row and a second stochastic bit stream received from a second stochastic translator translating a number encoded from a neuron in a column. A first storage is configured to store a weight value of the RPU, and a second storage is configured to store an amount of change to the weight value of the RPU. When the first stochastic bit stream and the second stochastic bit stream coincide, the amount of change to the weight value of the RPU is added to the weight value of the RPU.

Abstract: The disclosure is directed to optimizing parallel machine learning system design and performance using minibatch. A system for allocating data center resources according to embodiments includes: a machine learning process; a machine learning data set; a processing system including a P parallel processing elements for training the machine learning process using the machine learning data set, wherein the machine learning data set is split into a plurality of batches with a batch size M; and a resource manager for (1) minimizing a training time T=T(M,P) of the machine learning process over M for each value of P, and (2) efficient system design.

Abstract: The present application relates to systems for generating new variants from an existing corpus of documents and methods for using the same. The systems and methods generally comprise a corpus of documents and one or more types of variety provided by a user. The system generates one or more documents that are variants of the documents in the corpus of documents.

Abstract: Embodiments relate to supporting a decision making process. The method generates a graph that represents a decision making process. The graph comprises a plurality of nodes and a plurality of edges connecting the nodes. The nodes represent local decisions contributing to a global decision of the decision making process. Each node is associated with one or more parameters used for modeling the local decision. Each edge is associated with one or more parameters used for defining a relationship between two nodes. The method simulates the graph based at least in part on the parameters of the nodes and edges to derive an output global decision of the decision making process. The method receives a change to at least one of the parameters of the graph from a user and simulates the graph based at least in part on the at least one changed parameter to determine that the output global decision changes.

Abstract: Optimizing the performance of a machine learning system includes: defining an n-dimensional approximate computing configuration space, the n-dimensional approximate computing configuration space defining tuning parameters for tuning the machine learning system; setting a performance objective for the machine learning system that identifies one or more machine learning system performance criteria; collecting and monitoring performance data; comparing the performance data to the machine learning system performance objective; and dynamically updating the n-dimensional approximate computing configuration space by adjusting the at least one tuning parameter, in response to the comparison.

Abstract: A data processing system includes a user interface with a user input configured to enable a user to specify a type of simulation to be performed and at least one initial condition, where the simulation is executed using at least one sensor input from a grid structure composed of at least one of a power transmission and distribution grid. The user interface further has a display configured to visualize a representation of a result of a simulation of at least one scenario by presenting a multi-dimensional representation comprised of indicators, where each indicator corresponds to at least one simulation result. The user interface responds to a selection of one of the indicators by the user to visualize a result of the corresponding simulation. The type of simulation can be an N?k contingency analysis simulation, where k is equal to zero, 1 or greater than 1.

Abstract: An array of resistive processing units (RPUs) comprises a plurality of rows of RPUs and a plurality of columns of RPUs wherein each RPU comprises an AND gate configured to perform an AND operation of a first stochastic bit stream received from a first stochastic translator translating a number encoded from a neuron in a row and a second stochastic bit stream received from a second stochastic translator translating a number encoded from a neuron in a column. A first storage is configured to store a weight value of the RPU, and a second storage is configured to store an amount of change to the weight value of the RPU. When the first stochastic bit stream and the second stochastic bit stream coincide, the amount of change to the weight value of the RPU is added to the weight value of the RPU.

Abstract: Embodiments relate to supporting a decision making process. The method generates a graph that represents a decision making process. The graph comprises a plurality of nodes and a plurality of edges connecting the nodes. The nodes represent local decisions contributing to a global decision of the decision making process. Each node is associated with one or more parameters used for modeling the local decision. Each edge is associated with one or more parameters used for defining a relationship between two nodes. The method simulates the graph based at least in part on the parameters of the nodes and edges to derive an output global decision of the decision making process. The method receives a change to at least one of the parameters of the graph from a user and simulates the graph based at least in part on the at least one changed parameter to determine that the output global decision changes.

Abstract: Embodiments relate to supporting a decision making process. The method generates a graph that represents a decision making process. The graph comprises a plurality of nodes and a plurality of edges connecting the nodes. The nodes represent local decisions contributing to a global decision of the decision making process. Each node is associated with one or more parameters used for modeling the local decision. Each edge is associated with one or more parameters used for defining a relationship between two nodes. The method simulates the graph based at least in part on the parameters of the nodes and edges to derive an output global decision of the decision making process. The method receives a change to at least one of the parameters of the graph from a user and simulates the graph based at least in part on the at least one changed parameter to determine that the output global decision changes.

Abstract: Embodiments relate to supporting a decision making process. The method generates a graph that represents a decision making process. The graph comprises a plurality of nodes and a plurality of edges connecting the nodes. The nodes represent local decisions contributing to a global decision of the decision making process. Each node is associated with one or more parameters used for modeling the local decision. Each edge is associated with one or more parameters used for defining a relationship between two nodes. The method simulates the graph based at least in part on the parameters of the nodes and edges to derive an output global decision of the decision making process. The method receives a change to at least one of the parameters of the graph from a user and simulates the graph based at least in part on the at least one changed parameter to determine that the output global decision changes.

Abstract: A system, method and computer program product for generating probabilistic models of a subsurface region of the earth of interest. The system, method can be implemented efficiently to enable real-time imaging of a sub-surface structure. The system, method can provide users with the ability to assess where their subsurface images are reliable and where they are not in order to assist in the selection of low-risk, high-reward sights indicated as having oil potential for drilling. The system, method allows users to estimate a degree of uncertainty to be expected when drilling in a specific location. The knowledge of this uncertainly can be used to guide drilling in real-time to reduce the time to oil (and thereby the cost of drilling), increase the efficiency of drill maintenance and reduce the risk associated with incorrectly identifying the depth at which pressure might spike.

Abstract: A system, method and computer program product for seismic imaging implements a seismic modeling algorithm utilizing Forward Wave Inversion technique for revising Reverse Time Migration models used for sub-surface modeling. The technique requires large communication bandwidth and low latency to convert a parallel problem into one solved using massive domain partitioning. The partitioning of a velocity model into processing blocks allows each sub-problem to fit in a local cache, increasing locality and bandwidth and reducing latency. The RTM seismic data processing utilizes data that includes combined shot data, i.e., shot data selected from amongst a plurality of shots that are combined at like spatial points of the volume. An iterative approach is applied such that the correction term RTM generates at each iteration in the iterative approach is used for refining the model, and the updated model is used for generating a further refined RTM model.

Abstract: A system, method and computer program product for seismic imaging implements a seismic imaging algorithm utilizing Reverse Time Migration technique requiring large communication bandwidth and low latency to convert a parallel problem into one solved using massive domain partitioning. Several aspects of the imaging problem are addressed, including very regular and local communication patterns, balanced compute and communication requirements, scratch data handling and multiple-pass approaches. The partitioning of the velocity model into processing blocks allows each sub-problem to fit in a local cache, increasing locality and bandwidth and reducing latency. The RTM seismic data processing utilizes data that includes combined shot data, i.e., shot data selected from amongst a plurality of shots that are combined at like spatial points of the volume.

Abstract: A system, method and computer program product for seismic imaging implements a seismic imaging algorithm utilizing Reverse Time Migration technique requiring large communication bandwidth and low latency to convert a parallel problem into one solved using massive domain partitioning. Several aspects of the imaging problem, including very regular and local communication patterns, balanced compute and communication requirements, scratch data handling and multiple-pass approaches. The partitioning of the velocity model into processing blocks allows each sub-problem to fit in a local cache, increasing locality and bandwidth and reducing latency.

Abstract: A system and method implementing a hierarchical approach to RTM (Reverse Time Migration) seismic imaging at different granularity in space and time. An RTM seismic imaging algorithm utilizes RTM technique to convert a parallel problem into one solved using massive domain partitioning. In the method, a coarse-grain grid for the 3D volume of the geological subsurface structure under investigation is initially processed, permitting the RTM imaging process to be performed faster and produces lower level seismic image for inspection. Criteria are then applied to the first level of seismic image to determine whether to reject the image or whether a finer resolution seismic imaging is needed. In the case of finer resolution is needed, RTM resolution for the target volume is adjusted accordingly and RTM imaging process is applied with the new resolution. The process is repeated until either the image is accepted or rejected.

Abstract: A method is disclosed to simulate operation of a grid structure. The method includes specifying a type of simulation to be performed and at least one initial condition with a user interface of a device such as a mobile device, where the grid structure comprises at least one of a power generation grid and a power distribution grid. The method further includes transmitting the specified type of simulation and the at least one initial condition from the user device to a computing platform; receiving from the computing platform a result of the simulation at the user device; and visualizing the result of the simulation with the user interface. The type of simulation can be an N-k contingency analysis simulation, where k is equal to zero, 1 or greater than 1.

Abstract: A data processing system includes a user interface with a user input configured to enable a user to specify a type of simulation to be performed and at least one initial condition, where the simulation is executed using at least one sensor input from a grid structure composed of at least one of a power transmission and distribution grid. The user interface further has a display configured to visualize a representation of a result of a simulation of at least one scenario by presenting a multi-dimensional representation comprised of indicators, where each indicator corresponds to at least one simulation result. The user interface responds to a selection of one of the indicators by the user to visualize a result of the corresponding simulation. The type of simulation can be an N?k contingency analysis simulation, where k is equal to zero, 1 or greater than 1.