A signal encoder divides the signal into segments and uses prediction models to approximate the samples of each segment Each local prediction model, each applicable to one segment, is applied in its own translated axis system within the segment and the offset is given by the last predicted value for the previous segment. When the signal is reasonably continuous, it alleviates the need to parameterize the offset for each local predictor model as each local predictor model can build on this last predicted sample value of the previous segment. The encoder as a consequence doesn't suffer from a build up of error even though the offset is not transmitted but instead the last predicted value of the last sample of the previous segment is used. Prediction errors are obtained for the approximated samples and transmitted to the decoder, together with the predictor model parameters and seed value to allow accurate reconstruction of the signal by the decoder.

A node of a computing system includes a main memory and a plurality of processing core resources. The main memory includes a computing device section and a database section. The computing device section includes a computing device operating system area and a computing device general area. The database section includes a database section that includes a database operating system area, a disk area, a network area, and a database general area. The database operating system area allocates at least one portion of the main memory for database operations that is locked from access by the computing device operating system area.

Provided are a graph data compression method and apparatus. A computing device divides graph data including information about a source vertex and a destination vertex of an edge into a plurality of pieces, generates a plurality of compressed data obtained by compressing the plurality of pieces, and stores the plurality of compressed data as a file. The computing device may generate a plurality of pieces having a size equal to or less than a predefined data size by recursively dividing graph data.

A computing device includes a computing device controller hub and a plurality of parallelized nodes coupled to the computing device controller hub. Each node of the plurality of parallelized nodes includes a central processing module, a main memory, and at least one disk memory. The plurality of computing devices is operable to collectively execute query requests against at least one database table stored by the plurality of computing devices based on each node of each computing device performing corresponding operations independently from other nodes of the plurality of parallelized nodes.

A node includes a plurality of processing core resources. Each processing core resource of the plurality of processing core resources includes a corresponding processing module, a corresponding memory interface module, a corresponding memory device, and a corresponding cache memory. The plurality of processing core resources of the node is operable to collectively perform corresponding operations of the node. Each processing core resource of the plurality of processing core resources of the node is operable to perform operations independently from other ones of the plurality of processing core resources of the node.

A computing system is operable to generate a plurality of lines of coding blocks that includes a plurality of data blocks and a plurality of parity blocks. Each of the plurality of lines of coding blocks includes a corresponding subset of data blocks a corresponding subset of parity blocks. A set of segments of a segment group are generated to collectively include the plurality of lines of coding blocks. Different coding blocks of each of the plurality of lines of coding blocks are included within different ones of the set of segments, and the plurality of parity blocks are dispersed across all of the set of segments. The set of segments are stored via a plurality of nodes sets, where different segments of the set of segments are stored via memory resources of different node sets of the plurality of node sets.

This application a video file transcoding system and related transcoding method. The system includes: a segmentation device for obtaining a video file and a customized index parameter; split the video file into n video fragments; and generate transcoding configuration parameters according to the customized index parameter; a transcoding device for obtaining an i.sup.th video fragment; obtain a customized material corresponding to the i.sup.th video fragment according to the transcoding configuration parameters; add the customized material to the i.sup.th video fragment, to obtain an i.sup.th customized video fragment; and transcode the i.sup.th customized video fragment to obtain an i.sup.th target video fragment; and a merging device for merging n target video fragments into a target video file after n customized video fragments are all transcoded. This application resolves the problem that it takes too long to transcode a video file to which customized information needs to be added and/or transcoding efficiency is low.

Embodiments of the present disclosure pertain to point cloud data. In one embodiment, the present disclosure includes a computer implemented method comprising for compressing and storing point cloud data using a space-filling curve data structure and a dictionary space data structure. In another embodiment, the present disclosure includes applying a query against the data structures to retrieve point cloud data within a range.

Systems and methods are described herein for implementing a hybrid codec to compress and decompress image data using both lossy and lossless compression. In one example encoding process, it may be determined whether a first block of pixels of a frame of image data contains an edge. A type of compression by which to encode the first block may be selected based on that determination. The first block may be compressed using the selected type of compression. At least one second value associated with the first block of pixels may be set to indicate at least oof the compressed value or the type of compression used to compress the first block.

A computing system is operable to generate a first plurality of lines of coding blocks that includes a first plurality of data blocks and a first plurality of parity blocks. A first set of segments of a first segment group that collectively include the first plurality of lines of coding blocks are generated, and the first set of segments of the first segment group are stored via a first plurality of computing devices of a first storage cluster of the computing system. A second plurality of lines of coding blocks that includes a second plurality of data blocks and a second plurality of parity blocks are generated. A second set of segments of a second segment group that collectively include the second plurality of lines of coding blocks are generated. The second set of segments of the second segment group are stored via a second plurality of computing devices of a second storage cluster of the computing system.