Abstract: A computer-implemented method of object enhancement in endoscopy images includes capturing an image of an object within a surgical operative site via an imaging device, determining a size of the object based on the captured image of the object, displaying the captured image of the object, and displaying on the displayed captured image of the object a representation of the determined size of the object.

Abstract: A data analytics system stores a data file that includes an ordered set of data blocks. The data blocks can be parsed out of order. An error management module of the data analytics system detects a parse error occurring during parsing of a data block and generates an error message for the parse error. The error message includes unresolved location information indicating a location of the detected parse error in the data block. The error management module resolves the unresolved location information after determining that one or more additional data blocks preceding the data block in the ordered set have been parsed. The error management module generates resolved location information that indicates a location of the parse error in the data file. The error management module updates the error message with the resolved location information and outputs the updated error message.

Abstract: A data analytics system stores a plurality of sequential data blocks in a block cache. Each data block contains one or more data records. Each data record of a data record contains one or more values and a record marker marking the end of the data record. The data analytics system allocates a data block in the block cache to a worker thread. The worker thread parses the data block to identify the one or more data records contained within the data block. The data analytics system determines whether the data block was correctly parsed. Responsive to determining that the data block was correctly parsed, the data analytics system provides the one or more data records contained within the data block to a data analytics workflow.

Abstract: A module manages usage of a memory in a computer by scheduling data processing tasks. The module determines whether a memory associated with a computer is available for performing a data processing task. In response to determining that the memory is not available for performing the data processing task, the module generates a factory object for the data processing task. The factory object specifies instructions to produce the data processing task. After the factory object is generated, the module receives a request to perform the data processing task. The module produces the data processing task by using the factory object in response to the request and determine again whether the memory is available for performing the data processing task. In response to determining that the memory is now available for performing the data processing task, the module performs the data processing task by using the memory.

Abstract: Data records are joined using a computer. Data records in a first plurality of data records and a second plurality of data records are hashed. The data records in the first and second pluralities are respectively assigned to first and second groupings based on the hashes. Associated pairs of groupings from the first and second groupings are provided to a thread executing on a computer processor, and different pairs are provided to different threads. The threads operate on the pairs of groupings in parallel to determine whether to join the records in the groupings. A thread joins two data records under consideration if the hashes associated with the data records match. The joined data records are output.

Abstract: A data analytics system stores a data file that includes an ordered set of data blocks. The data blocks can be parsed out of order. An error management module of the data analytics system detects a parse error occurring during parsing of a data block and generates an error message for the parse error. The error message includes unresolved location information indicating a location of the detected parse error in the data block. The error management module resolves the unresolved location information after determining that one or more additional data blocks preceding the data block in the ordered set have been parsed. The error management module generates resolved location information that indicates a location of the parse error in the data file. The error management module updates the error message with the resolved location information and outputs the updated error message.

Abstract: A data analytics system stores a data file that includes an ordered set of data blocks. The data blocks can be parsed out of order. An error management module of the data analytics system detects a parse error occurring during parsing of a data block and generates an error message for the parse error. The error message includes unresolved location information indicating a location of the detected parse error in the data block. The error management module resolves the unresolved location information after determining that one or more additional data blocks preceding the data block in the ordered set have been parsed. The error management module generates resolved location information that indicates a location of the parse error in the data file. The error management module updates the error message with the resolved location information and outputs the updated error message.

Abstract: A module manages memory in a computer. The module monitors usage of a primary memory associated with the computer. The primary memory stores memory blocks in a ready state. In response to primary memory usage by the memory blocks in the ready state exceeding a ready state threshold, the module compresses at least some of the memory blocks in the ready state to form memory blocks in a ready and compressed state. In response to primary memory usage by the memory blocks in the ready and compressed state exceeding a release threshold, the module releases at least some of the memory blocks in the ready and compressed state. In response to primary memory usage by the memory blocks in the compressed state exceeding a compressed threshold, the module transfers at least some memory blocks in the compressed state to a secondary memory associated with the computer.

Abstract: A data analytics system stores a data file that includes an ordered set of data blocks. The data blocks can be parsed out of order. An error management module of the data analytics system detects a parse error occurring during parsing of a data block and generates an error message for the parse error. The error message includes unresolved location information indicating a location of the detected parse error in the data block. The error management module resolves the unresolved location information after determining that one or more additional data blocks preceding the data block in the ordered set have been parsed. The error management module generates resolved location information that indicates a location of the parse error in the data file. The error management module updates the error message with the resolved location information and outputs the updated error message.

Abstract: A data analytics system stores a plurality of sequential data blocks in a block cache. Each data block contains one or more data records. Each data record of a data record contains one or more values and a record marker marking the end of the data record. The data analytics system allocates a data block in the block cache to a worker thread. The worker thread parses the data block to identify the one or more data records contained within the data block. The data analytics system determines whether the data block was correctly parsed. Responsive to determining that the data block was correctly parsed, the data analytics system provides the one or more data records contained within the data block to a data analytics workflow.

Abstract: A module manages memory in a computer. The module monitors usage of a primary memory associated with the computer. The primary memory stores memory blocks in a ready state. In response to primary memory usage by the memory blocks in the ready state exceeding a ready state threshold, the module compresses at least some of the memory blocks in the ready state to form memory blocks in a ready and compressed state. In response to primary memory usage by the memory blocks in the ready and compressed state exceeding a release threshold, the module releases at least some of the memory blocks in the ready and compressed state. In response to primary memory usage by the memory blocks in the compressed state exceeding a compressed threshold, the module transfers at least some memory blocks in the compressed state to a secondary memory associated with the computer.

Abstract: Data records are joined using a computer. Data records in a first plurality of data records and a second plurality of data records are hashed. The data records in the first and second pluralities are respectively assigned to first and second groupings based on the hashes. Associated pairs of groupings from the first and second groupings are provided to a thread executing on a computer processor, and different pairs are provided to different threads. The threads operate on the pairs of groupings in parallel to determine whether to join the records in the groupings. A thread joins two data records under consideration if the hashes associated with the data records match. The joined data records are output.

Abstract: A module manages memory in a computer. The module monitors usage of a primary memory associated with the computer. The primary memory stores memory blocks in a ready state. In response to primary memory usage by the memory blocks in the ready state exceeding a ready state threshold, the module compresses at least some of the memory blocks in the ready state to form memory blocks in a ready and compressed state. In response to primary memory usage by the memory blocks in the ready and compressed state exceeding a release threshold, the module releases at least some of the memory blocks in the ready and compressed state. In response to primary memory usage by the memory blocks in the compressed state exceeding a compressed threshold, the module transfers at least some memory blocks in the compressed state to a secondary memory associated with the computer.

Abstract: A data analytics system stores a plurality of sequential data blocks in a block cache. Each data block contains one or more data records. Each data record of a data record contains one or more values and a record marker marking the end of the data record. The data analytics system allocates a data block in the block cache to a worker thread. The worker thread parses the data block to identify the one or more data records contained within the data block. The data analytics system determines whether the data block was correctly parsed. Responsive to determining that the data block was correctly parsed, the data analytics system provides the one or more data records contained within the data block to a data analytics workflow.

Abstract: Data records are joined using a computer. Data records in a first plurality of data records and a second plurality of data records are hashed. The data records in the first and second pluralities are respectively assigned to first and second groupings based on the hashes. Associated pairs of groupings from the first and second groupings are provided to a thread executing on a computer processor, and different pairs are provided to different threads. The threads operate on the pairs of groupings in parallel to determine whether to join the records in the groupings. A thread joins two data records under consideration if the hashes associated with the data records match. The joined data records are output.

Abstract: A data analytics system stores a plurality of sequential data blocks in a block cache. Each data block contains one or more data records. Each data record of a data record contains one or more values and a record marker marking the end of the data record. The data analytics system allocates a data block in the block cache to a worker thread. The worker thread parses the data block to identify the one or more data records contained within the data block. The data analytics system determines whether the data block was correctly parsed. Responsive to determining that the data block was correctly parsed, the data analytics system provides the one or more data records contained within the data block to a data analytics workflow.

Abstract: A module manages memory in a computer. The module monitors usage of a primary memory associated with the computer. The primary memory stores memory blocks in a ready state. In response to primary memory usage by the memory blocks in the ready state exceeding a ready state threshold, the module compresses at least some of the memory blocks in the ready state to form memory blocks in a ready and compressed state. In response to primary memory usage by the memory blocks in the ready and compressed state exceeding a release threshold, the module releases at least some of the memory blocks in the ready and compressed state. In response to primary memory usage by the memory blocks in the compressed state exceeding a compressed threshold, the module transfers at least some memory blocks in the compressed state to a secondary memory associated with the computer.

Abstract: Data records are joined using a computer. Data records in a first plurality of data records and a second plurality of data records are hashed. The data records in the first and second pluralities are respectively assigned to first and second groupings based on the hashes. Associated pairs of groupings from the first and second groupings are provided to a thread executing on a computer processor, and different pairs are provided to different threads. The threads operate on the pairs of groupings in parallel to determine whether to join the records in the groupings. A thread joins two data records under consideration if the hashes associated with the data records match. The joined data records are output.

Abstract: A data stream comprising a plurality of data records is retrieved. Portions of the data stream are aggregated to form a plurality of record packets of a predetermined size capacity. Each of the plurality of record packets comprises a number of data records from the plurality of data records. Further, the predetermined size capacity is an order of magnitude of a memory size of a cache memory associated with the data processing apparatus. Each of the plurality of record packets is transferred to respective ones of a plurality of threads associated with one or more processing operations. Each of the plurality of threads run independently on a respective processor from among a plurality of processors associated with the data processing apparatus.

Abstract: One or more embodiments provide a load balancing solution for improving the runtime performance of parallel HDL simulators. During compilation each process is analyzed to determine a simulation cost based on complexity of the HDL processes. During simulation, processes to be executed in the same simulation cycle are scheduled using the simulation costs computed at compile-time in order to reduce the delay incurred during simulation.