Embodiments of the present disclosure provide a method, an electronic device, and a computer program product for data processing. The method includes: determining, based on sizes of multiple data segments included in data to be processed, a first time required to perform a matching operation for each data segment, wherein the matching operation is used to determine non-duplicate data segments; determining, based on the size of each data segment and a compression level for the data to be processed, a second time required to perform a compression operation for each data segment; and determining, based on the first time, the second time, and a de-duplication rate for the data to be processed, a target mode for processing the multiple data segments from a first mode and a second mode, wherein in the first mode, a compression operation is performed only on the non-duplicate data segments in the multiple data segments, and in the second mode, a compression operation is performed on each of the multiple data segments. In this way, the data processing mode can be dynamically selected according to features of the data to be processed, thereby improving the efficiency of data processing.

A method, computer program product, and computer system for identifying, by a computing device, storage containers that contain cold data. At least a portion of the storage containers may be processed to determine whether a first compression technique will result in a higher level of compression above a threshold level of compression than a second compression technique. The storage containers may be processed using the first compression technique based upon, at least in part, determining that the first compression technique will result in the higher level of compression above the threshold level of compression than the second compression technique.

A train-linking lossless data compressor examines a block of data and uses a same coder to generate a same code when all data values in the input block are identical. When the input data is not all the same value, then a Gaussian coder, a Laplace coder, and a delta coder are activated in parallel. The three compressed code lengths are compared and the smallest code length is output as the compressed code when it is smaller than a copy code length. The copy code is a tag followed by copying all the data in the input block. When the smallest of the three compressed code lengths is larger than the copy code length, the file is not compressible, and the copy code is output. No frequency table is required so latency is low. The delta coder subtracts data values from an average value of the last data block.

One example method includes file specific compression selection. Compression metrics are generated for a chunk of a file. Using a set of training data, the compression metrics are corrected using a correction factor to determine estimated file compression metrics. A compressor is then selected to compress the file based on at least the estimated file compression metrics.

A subcutaneous and cutaneous electrocardiography monitor configured for self-optimizing ECG data compression is provided. The monitors include a housing, an electrocardiographic front end circuit, a memory, and a micro-controller configured to: obtain a series of electrode voltage values based on the sensed electrocardiographic signals; use a plurality of selection schemes to choose one or more of a plurality of compression algorithms associated with each of the selection scheme for testing; test the selected compression algorithms including applying the compression algorithms chosen using each of the selection schemes to a segment of the electrode voltage series; analyze results of the testing; select one or more compression algorithms chosen using one of the selection schemes for compressing at least a portion of the electrode voltage series based on the analysis; obtain a compression of at least the portion of the electrode voltage series; and store the compression within the memory.

Methods, apparatus, systems and articles of manufacture to compress data are disclosed. An example apparatus includes a data slicer to split a dataset into a plurality of blocks of data; a data processor to select a first compression technique for a first block of the plurality of blocks of data based on first characteristics of the first block; and select a second compression technique for a second block of the plurality of blocks of data based on second characteristics of the second block; a first compressor to compress the first block using the first compression technique to generate a first compressed block of data; a second compressor to compress the second block using the second compression technique to generate a second compressed block of data; and a header generator to generate a first header identifying the first compression technique and a second header identifying the second compression technique.

An accelerator or system including an accelerator can include an input interface to receive input data to be compressed and user application parameters for invocation of compression. The accelerator can include circuitry to identify a compression algorithm from configuration data provided with the input data. The user application parameters may not include parameters specifying entropy thresholds for compression of the input data. The circuitry can generate headers specific to the compression algorithm. The circuitry can generate uncompressed data blocks comprising blocks of the input data and corresponding headers. The circuitry can determine whether to provide the uncompressed data blocks or compressed data blocks based at least in part on entropy of the input data. Other methods, systems, and apparatuses are described.

A data compression method includes: obtaining a to-be-compressed object; searching a recommendation record for a recommended compression coding rule that meets a compression rate condition, the recommendation record being configured to record a compression coding rule of a historical compressed object and corresponding compression rate information, and the historical compressed object being of a same type as the to-be-compressed object; and if the recommended compression coding rule that meets the compression rate condition is found, compressing the to-be-compressed object by using the recommended compression coding rule; and if the recommended compression coding rule that meets the compression rate condition is not found, starting a regular compression coding process to obtain estimated compression rates of a plurality of compression coding rules for the to-be-compressed object, selecting a target compression coding rule based on at least the estimated compression rates, and compressing the to-be-compressed object by using the target compression coding rule.

A subcutaneous electrocardiography monitor configured for self-optimizing ECG data compression is provided. ECG waveform characteristics are rarely identical in patients with cardiac disease making this innovation crucial for the long-term data storage and analysis of complex cardiac rhythm disorders. The monitor includes a memory and a micro-controller operable to execute under a micro-programmable control and configured to: obtain a series of electrode voltage values; select one or more of a plurality of compression algorithms for compressing the electrode voltage series; apply one or more of the selected compression algorithms to the electrode voltage series; evaluate a degree of compression of the electrode voltage series achieved using the application of the selected algorithms; apply one or more of the compression algorithms to the compressed electrode voltage series upon the degree of compression not meeting a predefined threshold; and store the compressed electrode voltage series within the memory.

A decoder includes circuitry configured to receive a bitstream identify, in the bitstream, a current frame, wherein the current frame includes a plurality of regions, detect, in the bitstream, an indication that a first region is encoded according to a lossless encoding protocol and another region is encoded according to a lossy encoding protocol, and decode the current frame, wherein decoding the current frame further comprises decoding the first region using a lossless decoding protocol corresponding to the lossless encoding protocol.