The entropy coding of a current part of a predetermined entropy slice is based on, not only, the respective probability estimations of the predetermined entropy slice as adapted using the previously coded part of the predetermined entropy slice, but also probability estimations as used in the entropy coding of a spatially neighboring, in entropy slice order preceding entropy slice at a neighboring part thereof. Thereby, the probability estimations used in entropy coding are adapted to the actual symbol statistics more closely, thereby lowering the coding efficiency decrease normally caused by lower-delay concepts. Temporal interrelationships are exploited additionally or alternatively.

Methods and apparatus to parallelize data decompression are disclosed. An example method selecting initial starting positions in a compressed data bitstream; adjusting a first one of the initial starting positions to determine a first adjusted starting position by decoding the bitstream starting at a training position in the bitstream, the decoding including traversing the bitstream from the training position as though first data located at the training position is a valid token; outputting first decoded data generated by decoding a first segment of the bitstream starting from the first adjusted starting position; and merging the first decoded data with second decoded data generated by decoding a second segment of the bitstream, the decoding of the second segment starting from a second position in the bitstream and being performed in parallel with the decoding of the first segment, and the second segment preceding the first segment in the bitstream.

A data compressor with a hash computing hardware configured to evaluate the hash value for the current hash key extracted from a source data string, obtain a hash line corresponding to the hash value from a hash table, and perform hash key comparison to find at least one matching hash key. The hash line includes a prefix address column that stores a prefix address. Each entry of the hash line is provided to store a hash key and an offset. The hash computing hardware evaluates an address of the at least one matching hash key by combining the prefix address and an offset of the at least one matching hash key, and the offset of the at least one matching hash key is obtained from an entry storing the at least one matching hash key.

A method (C) for converting a data signal (U), comprising (i) providing an input symbol stream (B) representative of the data signal (U), (ii) demultiplexing (DMX) the input symbol stream (B) to consecutively decompose the input symbol stream (B) into a number m of decomposed partial symbol streams (B_1, . . . , B_m), (iii) applying on each of the decomposed partial symbol streams (B_1, . . . , B_m) an assigned distribution matching process (DM_1, . . . , DM_m), thereby generating and outputting for each decomposed partial symbol stream (B_1, . . . , B_m) a respective pre-sequence (bn_1, . . . , bn_m) or n_j symbols as an intermediate output symbol sequence, and (iv) supplying the pre-sequences (bn_1, . . . , bn_m) to at least one symbol mapping process (BM) to generate and output a signal representative for a final output symbol sequence (S) as a converted data signal. Each of the distribution matching processes (DM_1, . . . , DM_m) and the symbol mapping process (BM) are based on a respective assigned alphabet (ADM_1, . . . , ADM_m; ABM) of symbols, and the cardinality of each of the alphabets (ADM_1, . . . , ADM_m) of the distribution matching processes (DM_1, . . . , DM_m) is lower than the cardinality of the alphabet (ABM) of the symbol mapping process (BM).

A database-management system evaluates a query that retrieves and transforms encoded symbols stored in a database. If the stored symbols assume a relatively small set of distinct values, the system initially performs the transformation on every value in the set. During execution of subsequent queries, rather than performing the transformation upon every stored symbol fetched from the database, the system merely returns the previously derived encoded transformation results that correspond to the decoded value of each fetched symbol. If the symbols stored in the database span a relatively large set of distinct values, the system does not initially perform the transformation upon every value in the set. Instead, the first time the system fetches a symbol that has a particular value, it saves that symbol's encoded transformation result and reuses that result the next time it fetches an encoded symbol with the same value.

The entropy coding of a current part of a predetermined entropy slice is based on, not only, the respective probability estimations of the predetermined entropy slice as adapted using the previously coded part of the predetermined entropy slice, but also probability estimations as used in the entropy coding of a spatially neighboring, in entropy slice order preceding entropy slice at a neighboring part thereof. Thereby, the probability estimations used in entropy coding are adapted to the actual symbol statistics more closely, thereby lowering the coding efficiency decrease normally caused by lower-delay concepts. Temporal interrelationships are exploited additionally or alternatively.

A data packer is provided that is configured to form a bit stream for forwarding a plurality of values to memory. The bit stream includes the plurality of values and respective prefixes for identifying the values and the data packer is configured to insert the prefixes at predetermined boundaries in the bit stream, such that a prefix for identifying one value is inserted between bits that define a value identified by another prefix. A data unpacker is also provided that is configured to unpack a bit stream that comprises a plurality of values and respective prefixes for identifying those values that are located at predetermined boundaries in the bit stream, such that a prefix for identifying one value is inserted between bits that define a value identified by another prefix. The data unpacker is configured to identify a prefix at a predetermined boundary in the bit stream and determine, in dependence on that prefix and the predetermined boundaries, a location of the next prefix in the bit stream.

Systems and methods for stream-based compression include an encoder of a first device that may receive an input stream of bytes including a first byte preceded by one or more second bytes. The encoder may determine to identify a prefix code for the first byte. The encoder may select a prefix code table using the one or more second bytes. The encoder may identify, from the selected prefix code table, the prefix code of the first byte. The encoder may generate an output stream of bytes by replacing the first byte in the input stream with the prefix code of the first byte. The encoder may transmit the output stream from the encoder of the first device to a decoder of a second device. The output stream may have a fewer number of bits than the input stream.

Embodiments of the invention are directed to a DEFLATE compression accelerator and to a method for verifying the correctness of the DEFLATE compression accelerator. The accelerator includes an input buffer and a Lempel-Ziv 77 (LZ77) compressor communicatively coupled to an output of the input buffer. A switch is communicatively coupled to the output of the input buffer and to the output of the LZ77 compressor. The switch is configured to bypass the LZ77 compressor during a compression test. The accelerator further includes a deflate Huffman encoder communicatively coupled to an output of the switch and an output buffer communicatively coupled to the deflate Huffman encoder. When the switch is not bypassed, the compressor can be modified to produce repeatable results.

Input data can be losslessly reduced by using a data structure that organizes prime data elements based on their contents. Alternatively, the data structure can organize prime data elements based on the contents of a name that is derived from the prime data elements. Specifically, video data can be losslessly reduced by (1) using the data structure to identify a set of prime data elements, and (2) using the set of prime data elements to losslessly reduce intra-frames. The input data can be dynamically partitioned based on the memory usage of components of the data structure. Parcels can be created based on the partitions to facilitate archiving and movement of the data. The losslessly reduced data can be stored using a set of distilled files and a set of prime data element files.