Methods, systems, and computer programs for compressing nucleic acid sequence data. A method can include obtaining nucleic acid sequence data representing: (i) a read sequence, and (ii) a plurality of quality scores, determining whether the read sequence includes at least one “N” base, based on a determination that the read sequence includes at least one “N” base, generating, by one or more computers, a first encoding data set by using a first encoding process to encode each set of four quality scores of the read sequence into a single byte of memory, and using a second encoding process to encode the first encoded data set, thereby compressing the data to be compressed.

According to one embodiment, a data compression device includes a dictionary match determination unit, an extended matching generator, a match selector and a match connector. The dictionary match determination unit searches for first past input data matching first new input data. The extended matching generator compares second past input data subsequent to the first past input data with second new input data subsequent to the first new input data. The match selector generates compressed data by replacing a part of the input data with match information output from the dictionary match determination unit or the extended matching generator. The match connector replaces a plurality of match information in the compressed data with single match information.

To speed up decoding of a range code. A decompression circuit calculates a plurality of candidate bit values for each bit of the N-bit string based on a plurality of possible bit histories of a bit before a K-th bit in parallel for a plurality of bits, and repeatedly selects a correct bit value of the K-th bit from the plurality of candidate bit values based on a correct bit history of the bit before the K-th bit to decode the N-bit string.

One example method includes file specific compression selection. Compression metrics are generated for a chunk of a file. Using a set of training data, the compression metrics are corrected using a correction factor to determine estimated file compression metrics. A compressor is then selected to compress the file based on at least the estimated file compression metrics.

A method for executing computer programs in a trusted execution environment of a device is disclosed. The method includes retrieving a genomic differentiation object corresponding a computer program; modifying the genomic differentiation object based on genomic regulation instructions (GRI) to obtain a modified genomic differentiation object; and executing a first executable instruction of the computer program. Executing the first executable instruction includes: retrieving first encoded data that is input to the first executable instruction; extracting a sequence from metadata associated with the encoded data; generating a first genomic engagement factor (GEF) based on the first sequence, the GRI and, and the modified genomic differentiation object; decoding the first encoded data based on the first GEF to obtain first decoded data; and executing the first executable instruction using the first decoded data.

A method for executing computer programs in a trusted execution environment of a device is disclosed. The method includes retrieving a genomic differentiation object corresponding a computer program; modifying the genomic differentiation object based on genomic regulation instructions (GRI) to obtain a modified genomic differentiation object; and executing a first executable instruction of the computer program. Executing the first executable instruction includes: retrieving first encoded data that is input to the first executable instruction; extracting a sequence from metadata associated with the encoded data; generating a first genomic engagement factor (GEF) based on the first sequence, the GRI and, and the modified genomic differentiation object; decoding the first encoded data based on the first GEF to obtain first decoded data; and executing the first executable instruction using the first decoded data.

A disclosed information handling system includes an edge device communicatively coupled to a cloud computing resource. The edge device is configured to respond to receiving, from an internet of things (IoT) unit, a numeric value for a parameter of interest by determining a compressed encoding for the numeric value in accordance with a non-lossless compression algorithm. The edge device transmits the compressed encoding of the numeric value to the cloud computing resource. The cloud computing resource includes a decoder communicatively coupled to the encoder and configured to respond to receiving the compressed encoding by generating a surrogate for the numeric value. The surrogate may be generated in accordance with a probability distribution applicable to the parameter of interest. The compression algorithm may be a clustering algorithm such as a k-means clustering algorithm.

Decomposing a value range of the respective syntax elements into a sequence of n partitions with coding the components of z laying within the respective partitions separately with at least one by VLC coding and with at least one by PIPE or entropy coding is used to greatly increase the compression efficiency at a moderate coding overhead since the coding scheme used may be better adapted to the syntax element statistics. Accordingly, syntax elements are decomposed into a respective number n of source symbols s.sub.i with i=1 . . . n, the respective number n of source symbols depending on as to which of a sequence of n partitions into which a value range of the respective syntax elements is sub-divided, a value z of the respective syntax elements falls into, so that a sum of values of the respective number of source symbols s.sub.i yields z, and, if n>1, for all i=1 . . . n−1, the value of s.sub.i corresponds to a range of the i.sup.th partition.

Decomposing a value range of the respective syntax elements into a sequence of n partitions with coding the components of z laying within the respective partitions separately with at least one by VLC coding and with at least one by PIPE or entropy coding is used to greatly increase the compression efficiency at a moderate coding overhead since the coding scheme used may be better adapted to the syntax element statistics. Accordingly, syntax elements are decomposed into a respective number n of source symbols s.sub.i with i=1 . . . n, the respective number n of source symbols depending on as to which of a sequence of n partitions into which a value range of the respective syntax elements is sub-divided, a value z of the respective syntax elements falls into, so that a sum of values of the respective number of source symbols s.sub.i yields z, and, if n>1, for all i=1 . . . n−1, the value of s.sub.i corresponds to a range of the i.sup.th partition.

Technologies are provided for generation of programmable pulse signals using inverse chaotic maps, without reliance on a clocking signal. Some embodiments of the technologies include an apparatus that can receive a sequence of bits having a defined number of bits, where the sequence of bits represent a desired continuous pulse signal having a programmable width in time-domain. The apparatus can also can receive a precursor continuous pulse signal having an arbitrary width in time-domain that fits within the dynamic range of the apparatus. The apparatus can generate the desired continuous pulse signal by transforming the precursor continuous pulse signal using the sequence of bits and an inverse chaotic map.