Compressed domain processors configured to perform operations on data compressed in a format that preserves order. The Compressed domain processors may include operations such as addition, subtraction, multiplication, division, sorting, and searching. In some cases, compression engines for compressing the data into the desired formats are provided.

The present disclosure generally relates to an encoding scheme, and more specifically to a stable encoding scheme that is both variable-length and order-preserving. The present disclosure further describes a decoding scheme to decode and encoding generated by the encoding scheme. The encoding scheme may be parameterized by a single parameter k which remains constant across encoding and corresponding decoding operations. The output encodings generated by the encoding scheme are variable-length while maintaining order.

An encoder includes data processing hardware operable to: process input data into a plurality of blocks/packets; apply a plurality of transformations to content of the blocks/packets to generate corresponding transformed data; check a quality of representation of the transformed data prior to application of the transformations to determine whether or not the quality of representation of the transformed data satisfies quality criteria; if the quality of representation does not satisfy the quality criteria, to divide and/or combine the one or more individual blocks or packets further and repeating the transformation step; and if the quality of representation of the transformed data satisfies the one or more quality criteria, to select coding methods and encode data representative of the input data to be encoded to provide encoded output data; and communicate in the encoded data information describing the plurality of transformations or combinations of transformations employed when coding the blocks/packets.

According to one embodiment, a conversion device includes a demultiplexer, first to Nth extractors and a deinterleave unit. The demultiplexer extracts first to Nth substreams from a first compressed stream. The first to Nth substreams are placed in order in the first compressed stream and include first variable-length codes to Nth variable-length codes into which first symbols to Nth symbols of a symbol string have been converted. The first to Nth extractors extract the first variable-length codes to the Nth variable-length codes from the first to Nth substreams. The deinterleave unit reorders the first variable-length codes to the Nth variable-length codes in accordance with the symbol string and outputs a second compressed stream.

This disclosure provides methods, devices, and systems for data compression and decompression. The present implementations more specifically relate to entropy encoding and decoding techniques for keeping a state variable within upper and lower bounds using a noniterative process. The entropy encoding uses a fixed state threshold to determine a number of bits to remove and removes the bits from a current state prior to encoding a symbol with the current state. The entropy decoding decodes encoded data in a bitstream based on a current state to obtain the symbol and a new state and determines a number of bits to read from the bitstream and to add to the new state to update the current state.

A computing device includes a memory and a controller. The controller is configured to encrypt and/or compress a file by transforming at least a portion of said file to a number and transforming the number to an exponent vector comprising at least one exponent, wherein each exponent corresponds to a base in a base vector, whereby the file is represented by the exponent vector and a family constant. The family constant is configured to align the number to be compressed and/or encrypted into a table family number, and the table family number represents a number family which is evenly dividable with the number.

Compressed domain processors configured to perform operations on data compressed in a format that preserves order. The Compressed domain processors may include operations such as addition, subtraction, multiplication, division, sorting, and searching. In some cases, compression engines for compressing the data into the desired formats are provided.

The present invention discloses a waveform file processing method, storage medium, and device, wherein the method comprises a storage step, and such storage step comprises the following sub-steps: obtain a waveform file that comprises at least one waveform signal; assign a basic index value based on the waveform signal, and adopt the variable-length encoding method to, in a memory, encode the said waveform file as a resolvable serialized structure; when the memory consumed by the serialized structure reaches the threshold, trigger the compression and persistence for the current serialized structure, and obtain the waveform processing file. The present invention uses a unique organization mode to locally or remotely generate a waveform file of a specific format so that the efficiency of subsequent storage, reading, and debugging based on the waveform database file of the said format is significantly improved.

A lossless data compressor prevents normalization overruns on-the-fly as symbol occurrence counts are rounded to generate symbol frequencies, allowing an encoding table generator to generate encoding table entries without waiting for the symbol frequency table to finish filling. Rounding errors are accumulated as symbols are normalized and compensated for by reducing a symbol frequency when the symbol frequency is at least 2 and the accumulated errors have exceeded a threshold. The symbol frequency is also reduced when the number of remaining states in the encoding table is insufficient for a number of remaining unprocessed symbols and states for a current encoding table entry. Since error compensation occurs as symbols are being normalized, encoding table generation is not forced to wait for all symbols in the block to be processed, reducing latency. Three pipeline stages can operate on three input blocks: symbol counting, normalization/error compensation/encoding table generation, and data encoding.

Representative embodiments are disclosed for a rapid and highly parallel decompression of compressed executable and other files, such as executable files for operating systems and applications, having compressed blocks including run length encoded (RLE) data having data-dependent references. An exemplary embodiment includes a plurality of processors or processor cores to identify a start or end of each compressed block; to partially decompress, in parallel, a selected compressed block into independent data, dependent (RLE) data, and linked dependent (RLE) data; to sequence the independent data, dependent (RLE) data, and linked dependent (RLE) data from a plurality of partial decompressions of a plurality of compressed blocks, to obtain data specified by the dependent (RLE) data and linked dependent (RLE) data, and to insert the obtained data into a corresponding location in an uncompressed file. The representative embodiments are also applicable to other types of data processing for applications having data dependencies.