Abstract: A method of distributed resource management in a distributed computing system includes determining usage of respective hardware resources by an application and generating usage metrics for the application, and assigning the application to a cluster of hardware resources to optimize diversity of usage of hardware resources in the cluster and to enhance utilization of the hardware resources by applications running in that cluster. The diversity of usage of the hardware resources is determined from respective usage metrics of the respective applications running in that cluster. The diversity of usage of the hardware resources in the cluster is optimized by assigning the application to a diversity pool of hardware resources adapted to minimize interference when applications assigned to the diversity pool of hardware resources access the hardware resources in the diversity pool and assigning applications from different diversity pools to the cluster of hardware resources.

Abstract: A method of controlling an electronic device is provided, comprising receiving a selection contact within a first icon region of a first icon displayed on a pressure-sensing display screen of the electronic device, displaying on the pressure-sensing display screen a second set of icons related to the first icon, detecting that the selection contact uninterruptedly moves to a second icon of the second set of icons and selects the second icon, displaying on the pressure-sensing display screen a third set of icons related to the second icon, detecting that the selection contact uninterruptedly moves to a third icon of the third set of icons and selects the third icon, and initiating an application or function associated with the third icon.

Abstract: An apparatus and method are provided for review-based machine learning. Included are a non-transitory memory storing instructions and one or more processors in communication with the non-transitory memory. The one or more processors execute the instructions to receive first data, generate a plurality of first features based on the first data, and identify a first set of labels for the first data. A first model is trained using the first features and the first set of labels. The first model is reviewed to generate a second model, by receiving a second set of labels for the first data, and reusing the first features with the second set of labels in connection with training the second model.

Abstract: A method of distributed resource management in a distributed computing system includes determining usage of respective hardware resources by an application and generating usage metrics for the application, and assigning the application to a cluster of hardware resources to optimize diversity of usage of hardware resources in the cluster and to enhance utilization of the hardware resources by applications running in that cluster. The diversity of usage of the hardware resources is determined from respective usage metrics of the respective applications running in that cluster. The diversity of usage of the hardware resources in the cluster is optimized by assigning the application to a diversity pool of hardware resources adapted to minimize interference when applications assigned to the diversity pool of hardware resources access the hardware resources in the diversity pool and assigning applications from different diversity pools to the cluster of hardware resources.

Abstract: An apparatus and method are provided for a managed knowledge network platform (KNP). Model dissimilarity values for model pairs are obtained, each model pair including a first model of a plurality of models in a KNP and a different model in the plurality of models. Path lengths between a first model node of a plurality of model nodes in the KNP and each one of other model nodes are computed, where the first model node represents the first model and the first model node is connected to a first user node of a plurality of user nodes representing users of the KNP. At least one of the different models is selected based on the model dissimilarity values and the path lengths. A recommendation that includes the at least one model is generated for a first user represented by the first user node.

Abstract: A sender device includes a non-transitory memory storage comprising instructions and a location control policy, and a processor coupled to the memory. The processor executes the instructions to generate an email, generate a control mechanism for the email, wherein the control mechanism instructs a security server to implement the location control policy and wherein the location control policy affects a recipient device's use of the email, and integrate the control mechanism into the email to generate an integrated email. The sender device further includes a transmitter coupled to the processor and configured to transmit the integrated email to the security server for the security server to implement the control mechanism.

Abstract: System and method embodiments are provided for creating data structure for parallel programming. A method for creating data structures for parallel programming includes forming, by one or more processors, one or more data structures, each data structure comprising one or more global containers and a plurality of local containers. Each of the global containers is accessible by all of a plurality of threads in a multi-thread parallel processing environment. Each of the plurality of local containers is accessible only by a corresponding one of the plurality of threads. A global container is split into a second plurality of local containers when items are going to be processed in parallel and two or more local containers are merged into a single global container when a parallel process reaches a synchronization point.

Abstract: A system, computer readable medium, and method are provided for a resource management in a cloud architecture. The method includes the steps of collecting a first time stamped data (TSD), and a second TSD, and generating a prediction model based on the first TSD and the second TSD. The method further includes collecting a third TSD, and predicting a fourth TSD based on the prediction model and the third TSD. With more data are obtained via the prediction, the resource management is more efficient and accurate.

Abstract: In one embodiment, a method of false sharing detection includes performing, by a device, a plurality of optimization passes on source code, to produce optimized source code and receiving, by the device, selection criteria, The method also includes adding instrumentation to the optimized source code, by the device, after performing the plurality of optimization passes, to produce an instrumented code, where the instrumentation is configured to track memory access addresses and access types of global variables and heap variables in accordance with the selection criteria.

Abstract: In one embodiment, a method for predicting false sharing includes running code on a plurality of cores and determining whether there is potential false sharing between a first cache line and a second cache line, and where the first cache line is adjacent to the second cache line. The method also includes tracking the potential false sharing and reporting the potential false sharing.

Abstract: A method of controlling an electronic device is provided, comprising receiving a selection contact within a first icon region of a first icon displayed on a pressure-sensing display screen of the electronic device, displaying on the pressure-sensing display screen a second set of icons related to the first icon, detecting that the selection contact uninterruptedly moves to a second icon of the second set of icons and selects the second icon, displaying on the pressure-sensing display screen a third set of icons related to the second icon, detecting that the selection contact uninterruptedly moves to a third icon of the third set of icons and selects the third icon, and initiating an application or function associated with the third icon.

Abstract: A method for operating a multithread processing system is provided, including assigning, by a controller, a subset of a plurality of tasks to a plurality of threads during a time N, collecting, by the controller, data during the time N concerning the operation of the plurality of threads, analyzing, by the controller, the data to determine at least one condition concerning the operation of the plurality of threads during the time N, and adjusting, by the controller, a number of the plurality of threads available in time N+1 in accordance with the at least one condition.

Abstract: A system, computer readable medium, and method are provided for a resource management in a cloud architecture. The method includes the steps of collecting a first time stamped data (TSD), and a second TSD, and generating a prediction model based on the first TSD and the second TSD. The method further includes collecting a third TSD, and predicting a fourth TSD based on the prediction model and the third TSD. With more data are obtained via the prediction, the resource management is more efficient and accurate.

Abstract: A system, computer readable medium, and method are provided for reducing the power consumption of a mobile device. The method includes the steps of detecting video content to be viewed in an application executed by the mobile device; detecting unwanted content associated with the video content; and operating the mobile device in a low-power mode during playback of the video content in the application in response to detecting the unwanted content. The mobile device may include a memory storing the application and a processor executing the application, which configures the processor to implement the method. Five techniques may be applied in the low-power mode to reduce power consumption including Dynamic Voltage and Frequency Scaling (DVFS), reducing resolution of content, reducing brightness of a display, masking content, and thread throttling. The low-power mode saves energy when playing back videos on the mobile device.

Abstract: An apparatus and method are provided for a managed knowledge network platform (KNP). Model dissimilarity values for model pairs are obtained, each model pair including a first model of a plurality of models in a KNP and a different model in the plurality of models. Path lengths between a first model node of a plurality of model nodes in the KNP and each one of other model nodes are computed, where the first model node represents the first model and the first model node is connected to a first user node of a plurality of user nodes representing users of the KNP. At least one of the different models is selected based on the model dissimilarity values and the path lengths. A recommendation that includes the at least one model is generated for a first user represented by the first user node.

Abstract: An apparatus and method are provided for review-based machine learning. Included are a non-transitory memory storing instructions and one or more processors in communication with the non-transitory memory. The one or more processors execute the instructions to receive first data, generate a plurality of first features based on the first data, and identify a first set of labels for the first data. A first model is trained using the first features and the first set of labels. The first model is reviewed to generate a second model, by receiving a second set of labels for the first data, and reusing the first features with the second set of labels in connection with training the second model.

Abstract: A mobile device, computer readable medium, and method are provided for allocating resources within a cloud. The method includes the steps of collecting profile data from a plurality of resource agents and allocating a number of resource units to each resource agent in the plurality of resource agents based on the collected profile data. The allocating may be performed via a resource manager in communication with the plurality of resource agents.

Abstract: A mobile device, computer readable medium, and method are provided for allocating resources within a cloud. The method includes the steps of receiving metrics data associated with one or more tasks, training one or more models based on the metrics data to predict scores for tasks executed with a particular number of resource units, receiving a request that specifies a first task for processing a dataset, determining an optimal number of resource units to allocate to the first task based on predicted scores output by a first model, and allocating the optimal number of resource units to a resource agent in the cloud to manage the execution of the first task. The metrics data, which is collected by a plurality of cognitive agents, is received by a cognitive engine service in communication with the plurality of cognitive agents deployed in the cloud.

Abstract: A mobile device, computer readable medium, and method are provided for web browsing that reduces a power consumption of the mobile device. The method includes the steps of receiving a markup language document that includes a plurality of elements; assigning each element in the plurality of elements a priority value according to a set of rules; and selectively loading rendered content corresponding to the plurality of elements into a window of an application executed by the mobile device based on the priority value assigned to each element in the plurality of elements. The set of rules includes at least two rules configured to assign two or more priority values to at least two subsets of elements in the plurality of elements. Selective loading may refer to loading elements of a web page in a different order compared to a default order of a rendering engine of the web browser.

Abstract: A sender device includes a non-transitory memory storage comprising instructions and a temporal control policy, and a processor coupled to the memory. The processor executes the instructions to generate an email, generate a control mechanism for the email, wherein the control mechanism instructs a security server to implement the temporal control policy and wherein the temporal control policy affects a recipient device's use of the email, and integrate the control mechanism into the email to generate an integrated email. The sender device further includes a transmitter coupled to the processor and configured to transmit the integrated email to the security server for the security server to implement the control mechanism.