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.

Various embodiments include methods and devices for implementing compression of high dynamic ratio fields. Various embodiments may include receiving a compression block having data units, receiving a mapping for the compression block, wherein the mapping is configured to map bits of each data unit to two or more data fields to generate a first set of data fields and a second set of data fields, compressing the first set of data fields together to generate a compressed first set of data fields, and compressing the second set of data fields together to generate a compressed second set of data fields.

A method for processing image data and a system thereof are provided. The method is operated in the system including an encoding system and a decoding system. In the decoding system, multiple image data packages are received from the encoding system. The image data packages include multiple encoded data that are formed by encoding the pixels of an image and the pixels are beforehand rearranged according to an arrangement order. The arrangement order is exemplarily made based on the quantity of encoding circuits of the encoding system. In the decoding system, the encoded data received from the encoding system are sequentially stored in a memory according to the arrangement order. The decoding circuits start to decode the encoded data from an initial code synchronously for enhancing decoding performance. The method can be applied to decoding of high resolution images. The image is reproduced after the decoding process.

A system and method for a non-transient computer readable medium containing program instructions for causing a computer to perform a method for compressing data comprising the steps of receiving a data string for compression, the data string including a plurality of data elements, creating a template based on processing the data string, the template including common information across all data elements of the data string, creating one or more entries, wherein the one or more entries include information that is different to the template, and storing the template and the one or more entries.

Methods of image compression are described. A stream of color image data is filtered with a prediction routine using a pixel neighborhood. The filtered stream of color image data is sorted with a block sorting routing. A version of the color image data is compressed based on the sorted and filtered stream of color image data.

A method of data management in a data storage system including a plurality of data storage units, the method includes dividing each file in the data storage system into a plurality of blocks having a common size. The method further includes generating a hash value for each block using a common hash algorithm. The method further includes identifying a plurality of similar files in different data storage units, based on a comparison of the hashes for each file. The method further includes copying one or more of the identified similar files, such that similar files are stored in a single data storage unit and for one or more of the copied files, generating a link to a new location of the file. The method provides an efficient, effective, and adequate reduction of the primary storage as well as the secondary storage space.

Systems, methods, and apparatuses are provided for compressing values. A plurality of parameters may be obtained from a memory, each parameter comprising a floating-point number that is used in a relationship between artificial neurons or nodes in a model. A mantissa value and an exponent value may be extracted from each floating-point number to generate a set of mantissa values and a set of exponent values. The set of mantissa values may be compressed to generate a mantissa lookup table (LUT) and a plurality of mantissa LUT index values. The set of exponent values may be encoded to generate an exponent LUT and a plurality of exponent LUT index values. The mantissa LUT, mantissa LUT index values, exponent LUT, and exponent LUT index values may be provided to one or more processing entities to train the model.

A computer-implemented method for content-agnostic referencing of a binary data file, the method comprising: determining a length of the binary data file, the length comprising the number of bits of the binary data file; for the determined length, generating all permutations of data of the determined length; locating an index within the generated permutations, wherein the index is the starting position of the binary data file within the generated permutations; and using the length and the index to indicate the binary data file.

An image encoder includes a processor and a memory. The memory includes instructions configured to cause the processor to perform operations. In one example implementation, the operations may include determining whether a dictionary item is available for replacing a block of an image being encoded, the determining based on a hierarchical lookup mechanism, and encoding the image along with reference information of the dictionary item in response to determining that the dictionary item is available. In one more example implementation, the operations may include performing principal component analysis (PCA) on a block to generate a corresponding projected block, the block being associated with a group of images, comparing the projected block with a corresponding threshold, descending the block recursively based on the threshold until a condition is satisfied, and identifying a left over block as a cluster upon satisfying of the condition.

One example method includes receiving a mixed data stream that was created using a first data stream and a second data stream, the mixed data stream having a compressibility of N, where N is a compressibility merging parameter, and the mixed data stream has a compressibility that is between a compressibility of the first data stream and a compressibility of the second data stream, providing the mixed data stream to an application and/or hardware, observing and recording a response of the application and/or hardware to the mixed data stream, and analyzing the response of the response of the application and/or hardware to the mixed data stream.