Abstract: A stream of tuples to be processed by a plurality of processing elements operating on one or more computer processors are received. A first stream operator that is configured to perform a first operation on the received stream of tuples is identified by monitoring one or more stream operators in an operator graph. The first stream operator is determined to be a target operator. A field-programmable-gate-array (FPGA) card is determined to be configurable to perform the first operation. The FPGA card is determined to be available to perform the first operation. The FPGA card is added to the operator graph.

Abstract: A sequence of tuples, each having one or more attributes, is received at one of one or more processing elements operating on one or more processors. Each processing element may have one or more stream operators. A first stream operator may be identified as one that only processes an instance of a first attribute in a currently received tuple when a difference between an instance of the first attribute in a previously received tuple and the instance of the first attribute in the currently received tuple is outside of a difference threshold. A second stream operator may generate a difference attribute from a first instance of the first attribute in a first one of the received tuples and a second instance of the first attribute in a second one of the received tuples. The difference attribute may be transmitted from the second stream operator to the first stream operator.

Abstract: A web server includes a client pressure profile sharing and generation mechanism that detects when a user accesses the web server with a first device that does not have a client pressure profile, and automatically generates a client pressure profile for the first device from a client pressure profile for a second device used by the user. Adjustments may be automatically made to the client pressure profile for the first device based on differences in orientation and based on differences in screen size. Changes by the user to the client pressure profile for the first device can be automatically propagated to client pressure profiles for other devices used by the user.

Abstract: Multiple debug boundaries are defined in a hardware accelerator. The location of debug boundaries can be defined by a human user, or can be determined by automated tools based on characteristics of the circuitry in the hardware accelerator. Each debug boundary includes one or more hardware memory elements that are in a first state to indicate the debug boundary has not yet been reached, and that are changed to a second state by the hardware accelerator to indicate the debug boundary has been reached during execution of the hardware accelerator. Providing multiple debug boundaries in a hardware accelerator aids in debugging the accelerator design by identifying a particular section of the hardware accelerator where the failure occurred. This information regarding location of a failure may be provided to a user or to synthesis and simulation tools for the hardware accelerator design.

Abstract: A cloud-based hardware accelerator is selected by deploying an accelerator image to first and second clouds to generate first and second cloud-based hardware accelerators, executing a first request on the first and second cloud-based hardware accelerators, monitoring characteristics of the first and second cloud-based hardware accelerators executing the first request, which may include execution time and monetary cost, and selecting one of the first and second hardware accelerators according to defined selection criteria. Subsequent requests are then routed to the selected cloud-based accelerator.

Abstract: A processor may determine, using natural language processing, a writing style of content of a composed message written by a composer. The processor may analyze, using natural language processing, a set of previous message written by the composer. The processor may identify, based on the analyzing, writing habits of the composer. The processor may also identify a difference between the writing style of the content and the writing habits of the composer. The processor may display a notification of the difference to the user.

Abstract: Embodiments presented herein describe techniques for tracking operators of a distributed computing environment (e.g., a streams processing environment) using metadata. During execution of a distributed application of the computing environment, a tracker tool monitors a plurality of operators of the distributed application. Each of the operators stores one or more specified metadata values associated with the operator. For each operator, the tracker tool retrieves the one or more specified metadata values associated with the operator. Upon determining that one of the one or more specified metadata values do not comply with a corresponding expected metadata value, the tracker tool generates an indicator for the operator. The indicator includes information describing the one or more specified metadata values.

Abstract: A memory manager on a programmable device manages memory allocated to accelerators on the programmable device and allocated to processes that access the programmable device. The memory manager can manage both memory on the programmable device as well as external memory coupled to the programmable device. The memory manager protects the memory from unauthorized access by enforcing protection for the memory, using keys, encryption or the like. The memory manger can allocate a partition of memory to an accelerator when an accelerator is deployed to a programmable device, then allocate subpartitions within the allocated partition for each process that accesses the accelerator. When an accelerator is cast out of the programmable device, the memory partition is scrubbed so it can be reclaimed and allocated to another accelerator. When a process terminates, the subpartitions corresponding to the process are scrubbed so they may be reclaimed and allocated to another process.

Abstract: A cloud-based accelerator manager manages cloud-based hardware accelerators. The accelerator manager monitors computer programs running in the cloud and generates a trace that indicates which accelerators were used and when. The trace may be for a single computer program or may be for multiple computer programs. Thus, the trace can be program-specific, showing all accesses to accelerators by a single program, or may be accelerator-specific, showing all accesses to each accelerator by all computer programs. The cloud-based accelerator manager detects a failure in one of the computer programs executing in the cloud. The cloud-based accelerator manager provides the trace to a user, who can then analyze the trace to determine whether the failure was due to an accelerator. The cloud-based accelerator manager thus helps detect when cloud-based accelerators are the reason for failures for computer programs running in a cloud.

Abstract: A debugger for distributed software running on multiple computer systems analyzes and compares system environments for the multiple computer systems. When a breakpoint occurs, or when a failure in one of the computer systems occurs, the debugger determines when one or more values of interest in the distributed software differ among the different computer systems. The debugger then determines whether the one or differing values correlate to the system environment for the corresponding computer systems. When the one or more differing values correlate to the system environment for the corresponding computer systems, the user of the debugger is notified of the correlation between the differing values and the system environments of the computer systems, to help potentially identify differences in system environments that could be contributing to the differing values.

Abstract: A system and method for modifying a feature of a device based on an applied touch intensity is disclosed. When a touch is received, a sensor component sends a signal to a measurement component. The measurement component converts the signal into a touch intensity and provides the determined touch intensity to a selection component. The selection component selects at least one action from a set of actions to be executed by the device based on the determined touch intensity.

Abstract: High speed optoelectronic devices and associated methods are provided. In one aspect, for example, a high speed optoelectronic device can include a silicon material having an incident light surface, a first doped region and a second doped region forming a semiconductive junction in the silicon material, and a textured region coupled to the silicon material and positioned to interact with electromagnetic radiation. The optoelectronic device has a response time of from about 1 picosecond to about 5 nanoseconds and a responsivity of greater than or equal to about 0.4 A/W for electromagnetic radiation having at least one wavelength from about 800 nm to about 1200 nm.

Abstract: A remote visual experience application which transmits real-time video remotely includes a filter which obscures one or more previously identified regions in space when the regions come within the camera's field of vision. The application may be a shared visual experience application, in which the camera is mounted to a wearable appliance of a local user. The application may include a function for mapping regions of a space in which the application will be used, and defining different levels of remote access for different regions of the space. A space map may be generated before or during transmission of video to a remote user. Exemplary embodiments include a virtual vendor house call application or a game. The application may further include an audio filter for filtering an audio signal.

Abstract: A cloud-based accelerator manager manages cloud-based hardware accelerators. The accelerator manager monitors computer programs running in the cloud and generates a trace that indicates which accelerators were used and when. The trace may be for a single computer program or may be for multiple computer programs. Thus, the trace can be program-specific, showing all accesses to accelerators by a single program, or may be accelerator-specific, showing all accesses to each accelerator by all computer programs. The cloud-based accelerator manager detects a failure in one of the computer programs executing in the cloud. The cloud-based accelerator manager provides the trace to a user, who can then analyze the trace to determine whether the failure was due to an accelerator. The cloud-based accelerator manager thus helps detect when cloud-based accelerators are the reason for failures for computer programs running in a cloud.

Abstract: An accelerator manager monitors run-time performance of multiple accelerators in one or more programmable devices, and when first and second accelerators satisfy at least one coalescence criterion, the accelerator manager generates a new accelerator image corresponding to a third accelerator that coalesces the first accelerator and the second accelerator. In a first embodiment, the accelerator manager generates the new accelerator image from the accelerator images for the first and second accelerators. In a second embodiment, the accelerator manager generates the new accelerator image from hardware description language representations of the first and second accelerators. The new accelerator image is deployed to a programmable device to provide a new accelerator, and calls to the first and second accelerators are replaced with calls to the new accelerator.

Abstract: A processor may determine, using natural language processing, a writing style of content of a composed message written by a composer. The processor may analyze, using natural language processing, a set of previous message written by the composer. The processor may identify, based on the analyzing, writing habits of the composer. The processor may also identify a difference between the writing style of the content and the writing habits of the composer. The processor may display a notification of the difference to the user.

Abstract: A method, system and computer program product are provided for implementing enhanced autocomplete via multiple mobile keyboards. A user input is mapped to other keys to identify a meaningful message. When a meaningful message is not identified, the user input is compared with text using other keyboards for the mobile device. When a meaningful message is identified, the user input is automatically corrected.

Abstract: A code portion in a computer program is identified that will be improved from being deployed to a hardware accelerator to enhance the run-time performance of the computer program. An accelerator catalog includes a listing of currently-implemented accelerators, along with available resources on one or more programmable devices. When the catalog does not include the needed accelerator, the available resources are determined from the catalog, and when the available resources are insufficient to deploy the needed accelerator, one or more of the existing accelerators is cast out of the programmable device according to specified ranking criteria to make room for the needed accelerator. The needed accelerator image is dynamically generated and deployed, the identified code portion of the computer program is replaced with a call to the deployed hardware accelerator, the newly-generated accelerator is stored in the catalog, and the available resources data in the catalog is updated.

Abstract: An accelerator manager monitors one or more requests for accelerators from one or more users, and deploys one or more accelerators to one or more programmable devices based on the one or more requests from the one or more users. In a first embodiment, the accelerator manager deploys an accelerator that satisfies multiple user requests. The multiple user requests can be multiple requests from one user, or could be multiple requests from multiple users. In a second embodiment, the accelerator manager compiles historical data from the monitored requests, identifies one or more accelerators that are requested following the request for a first accelerator, and deploys the one or more accelerators after the first accelerator is requested and before they are requested.

Abstract: An accelerator manager validates an accelerator image using one or more suitable validation methods, which may include comparing results of running an accelerator with results of simulating the accelerator, comparing results of running an accelerator on two different programmable devices, and deploying the accelerator to a cloud of an accelerator provider and running the accelerator to determine whether the accelerator meets defined specifications. The accelerator manager can also report information about one or more accelerators to an accelerator provider and/or to a provider of a programmable device.