Technologies for providing shared memory for accelerator sleds includes an accelerator sled to receive, with a memory controller, a memory access request from an accelerator device to access a region of memory. The request is to identify the region of memory with a logical address. Additionally, the accelerator sled is to determine from a map of logical addresses and associated physical address, the physical address associated with the region of memory. In addition, the accelerator sled is to route the memory access request to a memory device associated with the determined physical address.

According to one embodiment, a memory system includes a first compression unit, a second compression unit, a non-volatile memory, a first decoding unit, a conversion unit and an output unit. The first compression unit is configured to output second data obtained by compressing first data. The second compression unit is configured to output third data obtained by compressing the second data. Fourth data based on the third data is written to the non-volatile memory. The first decoding unit is configured to decode the third data based on the fourth data to the second data. The conversion unit is configured to acquire fifth data by converting a format of the second data. The output unit is configured to output the fifth data to a host.

A processor includes a memory hierarchy, buffer, and a decompressor. The decompressor includes circuitry to read elements to be decompressed according to a compression scheme, parse the elements to identify literals and matches, and, with the literals and matches, generate an intermediate token stream formatted for software-based copying of the literals and matches to produce decompressed data. The intermediate token stream is to include a format for multiple tokens that are to be written in parallel with each other, and another format for tokens that include a data dependency upon themselves.

Certain implementations of the disclosed technology may include methods and computing systems for performing high-density data compression, particularly on numerical data that demonstrates various patterns, and patterns of patters. According to an example implementation, a method is provided. The method may include extracting a data sample from a data set, compressing the data sample using a first compression filter configuration, and calculating a compression ratio associated with the first compression filter configuration. The method may also include compressing the data sample using a second compression filter configuration and calculating a compression ratio associated with the second compression filter configuration. A particular compression filter configuration to utilize in compressing the entire data set may be selected based on a comparison of the compression ratio associated with the first compression filter configuration and a compression ratio associated with the second compression filter configuration.

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.

Disclosed are a communication technique which merges, with IoT technology, a 5G communication system for supporting a data transmission rate higher than that of a 4G system, and a system therefor. The present disclosure can be applied to intelligent services (for example, smart homes, smart buildings, smart cities, smart cars or connected cars, healthcare, digital education, retail, security- and safety-related services, and the like) on the basis of 5G communication technology and IoT-related technology. Disclosed are a method and apparatus for driving a PDCP layer apparatus during data decompression failure in a next-generation mobile communication system.

A method for compressing a first application file and second application file includes accessing the first and the second application files, the first application file being in a first language and the second application being in a second language and being a counterpart of the first application file, decompressing the first and second application files to access internal files for the first and the second application files, comparing one of the first internal files to one of the second internal files, upon determining that the first internal file is identical to the second internal file, copying one of the internal files to an output folder, and upon determining that the files are not identical, copying both of the internal files to the output folder, or executing a differencing procedure on the first and second internal files to identify differences between them, storing data about the differences in the output folder, and compressing the output folder into one output file.

Methods, computer program products, and/or systems are provided that perform the following operations: in a data replication environment, analyzing a database workload to generate a knowledge base of information related to compression; dividing a transfer data stream into different segments based, at least in part, on the knowledge base; obtaining candidate compression types for the transfer data stream based, at least in part, on the knowledge base; assigning respective compression types of the candidate compression types to the different segments; generating compressed segments based, at least in part, on the respective compression types assigned to the different segments; and providing the compressed segments to a replication target.

An electronic device that includes a decompression engine that includes N decoders and a decompressor decompresses compressed input data that includes N streams of data. Upon receiving a command to decompress compressed input data, the decompression engine causes each of the N decoders to decode a respective one of the N streams from the compressed input data separately and substantially in parallel with others of the N decoders. Each decoder outputs a stream of decoded data of a respective type for generating commands associated with a compression standard for decompressing the compressed input data. The decompressor next generates, from the streams of decoded data output by the N decoders, commands for decompressing the data using the compression standard to recreate the original data. The decompressor next executes the commands to recreate the original data and stores the original data in a memory or provides the original data to another entity.

Certain implementations of the disclosed technology may include methods and computing systems for performing high-density data compression, particularly on numerical data that demonstrates various patterns, and patterns of patters. According to an example implementation, a method is provided. The method may include extracting a data sample from a data set, compressing the data sample using a first compression filter configuration, and calculating a compression ratio associated with the first compression filter configuration. The method may also include compressing the data sample using a second compression filter configuration and calculating a compression ratio associated with the second compression filter configuration. A particular compression filter configuration to utilize in compressing the entire data set may be selected based on a comparison of the compression ratio associated with the first compression filter configuration and a compression ratio associated with the second compression filter configuration.