H03M7/42

DEFLATE COMPRESSION USING SUB-LITERALS FOR REDUCED COMPLEXITY HUFFMAN CODING
20220416811 · 2022-12-29 ·

An input sequence that has a plurality of bits is received where the input sequence is associated with a first section of data within a compressed block. The plurality of bits in the input sequence are divided into a first sub-sequence comprising a first set of bits and a second sub-sequence comprising a second set of bits. The first sub-sequence is encoded using a first Huffman code tree to obtain a first codeword and the second sub-sequence is encoded using a second Huffman code tree to obtain a second codeword. Encoded data that includes information associated with the first Huffman code tree, information associated with the second Huffman code tree, the first codeword, and the second codeword is output.

Data compression transmission system, intermediate server, method, and program

A technique for compressing and transmitting data without hampering real-time performance can be offered. In a data compression transmission system for collecting data generated by a plurality of devices at a central server via a network, an intermediate server is arranged between the devices and the central server. Each of the devices includes a packet cache processing unit for converting the generated data to a hash value based on a cache. The intermediate server includes a packet cache processing unit for decoding the hash value to original data based on the cache, a buffering unit for aggregating the data and outputting the data as a long packet, and a compression encoding unit for compressing the data and generating encoded data.

Data compression transmission system, intermediate server, method, and program

A technique for compressing and transmitting data without hampering real-time performance can be offered. In a data compression transmission system for collecting data generated by a plurality of devices at a central server via a network, an intermediate server is arranged between the devices and the central server. Each of the devices includes a packet cache processing unit for converting the generated data to a hash value based on a cache. The intermediate server includes a packet cache processing unit for decoding the hash value to original data based on the cache, a buffering unit for aggregating the data and outputting the data as a long packet, and a compression encoding unit for compressing the data and generating encoded data.

GUARANTEED DATA COMPRESSION USING INTERMEDIATE COMPRESSED DATA
20220286142 · 2022-09-08 ·

Methods for converting an n-bit number into an m-bit number for situations where n>m and also for situations where n<m, where n and m are integers. The methods use truncation or bit replication followed by the calculation of an adjustment value which is applied to the replicated number.

TECHNOLOGIES FOR PROVIDING MANIFEST-BASED ASSET REPRESENTATION

Technologies for generating manifest data for a sled include a sled to generate manifest data indicative of one or more characteristics of the sled (e.g., hardware resources, firmware resources, a configuration of the sled, or a health of sled components). The sled is also to associate an identifier with the manifest data. The identifier uniquely identifies the sled from other sleds. Additionally, the sled is to send the manifest data and the associated identifier to a server. The sled may also detect a change in the hardware resources, firmware resources, the configuration, or component health of the sled. The sled may also generate an update of the manifest data based on the detected change, where the update specifies the detected change in the hardware resources, firmware resources, the configuration, or component health of the sled. The sled may also send the update of the manifest data to the server.

TECHNOLOGIES FOR PROVIDING MANIFEST-BASED ASSET REPRESENTATION

Technologies for generating manifest data for a sled include a sled to generate manifest data indicative of one or more characteristics of the sled (e.g., hardware resources, firmware resources, a configuration of the sled, or a health of sled components). The sled is also to associate an identifier with the manifest data. The identifier uniquely identifies the sled from other sleds. Additionally, the sled is to send the manifest data and the associated identifier to a server. The sled may also detect a change in the hardware resources, firmware resources, the configuration, or component health of the sled. The sled may also generate an update of the manifest data based on the detected change, where the update specifies the detected change in the hardware resources, firmware resources, the configuration, or component health of the sled. The sled may also send the update of the manifest data to the server.

RELATIONAL METHOD FOR TRANSFORMING UNSORTED SPARSE DICTIONARY ENCODINGS INTO UNSORTED-DENSE OR SORTED -DENSE DICTIONARY ENCODINGS
20220284005 · 2022-09-08 ·

Unsorted sparse dictionary encodings are transformed into unsorted-dense or sorted-dense dictionary encodings. Sparse domain codes have large gaps between codes that are adjacent in order. Unlike spare codes, dense codes have smaller gaps between adjacent codes; consecutive codes are dense codes that have no gaps between adjacent codes. The techniques described herein are relational approaches that may be used to generate sparse composite codes and sorted codes.

ENTROPY CODING SUPPORTING MODE SWITCHING

A decoder for decoding a data stream into which media data is coded has a mode switch configured to activate a low-complexity mode or a high-efficiency mode depending on the data stream, an entropy decoding engine configured to retrieve each symbol of a sequence of symbols by entropy decoding using a selected one of a plurality of entropy decoding schemes, a desymbolizer configured to desymbolize the sequence of symbols to obtain a sequence of syntax elements, a reconstructor configured to reconstruct the media data based on the sequence of syntax elements, selection depending on the activated low-complexity mode or the high-efficiency mode. In another aspect, a desymbolizer is configured to perform desymbolization such that the control parameter varies in accordance with the data stream at a first rate in case of the high-efficiency mode being activated and the control parameter is constant irrespective of the data stream or changes depending on the data stream, but at a second lower rate in case of the low-complexity mode being activated.

ENTROPY CODING SUPPORTING MODE SWITCHING

A decoder for decoding a data stream into which media data is coded has a mode switch configured to activate a low-complexity mode or a high-efficiency mode depending on the data stream, an entropy decoding engine configured to retrieve each symbol of a sequence of symbols by entropy decoding using a selected one of a plurality of entropy decoding schemes, a desymbolizer configured to desymbolize the sequence of symbols to obtain a sequence of syntax elements, a reconstructor configured to reconstruct the media data based on the sequence of syntax elements, selection depending on the activated low-complexity mode or the high-efficiency mode. In another aspect, a desymbolizer is configured to perform desymbolization such that the control parameter varies in accordance with the data stream at a first rate in case of the high-efficiency mode being activated and the control parameter is constant irrespective of the data stream or changes depending on the data stream, but at a second lower rate in case of the low-complexity mode being activated.

Relational method for transforming unsorted sparse dictionary encodings into unsorted-dense or sorted-dense dictionary encodings

Unsorted sparse dictionary encodings are transformed into unsorted-dense or sorted-dense dictionary encodings. Sparse domain codes have large gaps between codes that are adjacent in order. Unlike spare codes, dense codes have smaller gaps between adjacent codes; consecutive codes are dense codes that have no gaps between adjacent codes. The techniques described herein are relational approaches that may be used to generate sparse composite codes and sorted codes.