Described herein is a system that facilitates recommending data compression using machine learning and statistical attributes. According to an embodiment, a system can comprise receiving a dataset, statistical attributes associated with the dataset, and a compression requirement for compression of the dataset. The system can further comprise based on the statistical attributes and the compression requirement, estimating a first compression attribute and a second compression attribute of a group of compression processes. The system can further comprise selecting a primary compression process from the group of compression processes, based on an output of an analytics component, wherein the analytics component employs a neural network to determine the primary compression process based on analysis of the statistical attributes, the compression requirement, and a compression objective.

This disclosure relates to data storage in a blockchain-type ledger storing data based on a blockchain data structure. In one aspect, a method includes obtaining service data. A compression threshold on which selection of a target object for performing data compression is based is determined. The target object includes a client device or a database server. At least one of a hardware performance parameter or a network performance parameter is obtained. A compression weight is determined based on at least one of the hardware performance parameter or the network performance parameter. When the compression weight is greater than a predetermined value, data compression is performed on the service data at the client device. When the compression weight is less than or equal to the predetermined value, the client device sends the service data to the database server so that the database server performs data compression on the service data.

An electronic device includes at least one compression-decompression functional block and a hierarchy of cache memories with a first cache memory and a second cache memory. The at least one compression-decompression functional block receives data in an uncompressed state, compresses the data using one of a first compression or a second compression, and, after compressing the data, provides the data to the first cache memory for storage therein. When the data is retrieved from the first cache memory to be stored in the second cache memory, when the data is compressed using the first compression, the compression-decompression functional block decompresses the data to reverse effects of the first compression on the data, thereby restoring the data to the uncompressed state and provides the data compressed using the second compression or in the uncompressed state to the second cache memory for storage therein.

A method for compressing data in a local cache of a web server is described. A local cache compression engine accesses values in the local cache and determines a cardinality of the values of the local cache. The local cache compression engine determines a compression rate of a compression algorithm based on the cardinality of the values of the local cache. The compression algorithm is applied to the cache based on the compression rate to generate a compressed local cache.

A transmitting apparatus is provided for transmitting data to a receiving apparatus, the transmitting apparatus comprising: a first network interface configured to transmit data to the receiving apparatus over a first communications path; a transmit buffer forming part of the first network interface, the transmit buffer being configured to store a series of packets of data for transmission over the first communications path; a data compression module configured to compress at least some of the packets of data stored for transmission; a second network interface configured to receive a decompression rate value from the receiving apparatus over a second communications path; and wherein the apparatus is configured to select data packets stored in the transmit buffer for compression based on a compression rate value and a transmission rate value of the transmitting apparatus and a decompression rate value received from the receiving apparatus via the second network interface. A receiving apparatus is also provided.

A method, and the associated design, schema and techniques for processing digital data, whether random or not, through encoding and decoding losslessly and correctly for purposes of encryption/decryption or compression/decompression or both, including the use of Digital Lensing, Unlimited Code System, and other associated techniques. There is no assumption of or requirement for the digital information to be processed before processing.

A system and a method provide compression and decompression of an activation map of a layer of a neural network. For compression, the values of the activation map are sparsified and the activation map is configured as a tensor having a tensor size of HWC in which H represents a height of the tensor, W represents a width of the tensor, and C represents a number of channels of the tensor. The tensor is formatted into at least one block of values. Each block is encoded independently from other blocks of the tensor using at least one lossless compression mode. For decoding, each block is decoded independently from other blocks using at least one decompression mode corresponding to the at least one compression mode used to compress the block; and deformatted into a tensor having the size of HWC.

The disclosure herein provides techniques for designing cache compression algorithms that control how data in caches are compressed. The techniques generate a custom byte select algorithm by applying repeated transforms applied to an initial compression algorithm until a set of suitability criteria is met. The suitability criteria include that the cost is below a threshold and that a metadata constraint is met. The cost is the number of blocks that can be compressed by an algorithm as compared with the ideal algorithm. The metadata constraint is the number of bits required for metadata.

A method performed by a network node (110) is described herein. The method is for managing compression of information to be transmitted by a transmitting device (130) 5 in a set of packets. The network node (110) determines (304) whether or not to apply a first compression algorithm to the information comprised in the set of packets. The determining (304) is based on at least one of: i) a compression efficiency of the first compression algorithm applied to a first information comprised in a first set of packets, and ii) a computational complexity of the first algorithm. The information is a second 10 information and the set of packets is a second set of packets. Each of the first and the second set of packets comprise at least one packet. The network node (110) then initiates (305) providing, based on a result of the determination, an indication of the result to the transmitting device (130).

An information processing apparatus includes: a processor; and a processing circuit coupled to the processor, wherein the processing circuit is configured to: generate compressed data by compressing send data; and determine whether to transmit the compressed data or the send data before the compression to a network, based on a size of the compressed data, and wherein the processor is configured to transmit the compressed data or the send data before the compression to the network, based on a result of the determination.