Technologies for switching network traffic include a network switch. The network switch includes one or more processors and communication circuitry coupled to the one or more processors. The communication circuitry is capable of switching network traffic of multiple link layer protocols. Additionally, the network switch includes one or more memory devices storing instructions that, when executed, cause the network switch to receive, with the communication circuitry through an optical connection, network traffic to be forwarded, and determine a link layer protocol of the received network traffic. The instructions additionally cause the network switch to forward the network traffic as a function of the determined link layer protocol. Other embodiments are also described and claimed.

The generation of symbol-encoded data from digital data, as part of the compression of the digital data into a compressed digital data, can be performed with reference to multiple alternative alphabets. A selection of a specific alphabet is made based on the digital data being compressed, the compression parameters, or combinations thereof. Information indicative of the selected alphabet is encoded into one or more headers of the resulting compressed digital data. A single alphabet can be selected for all of a set of digital data being compressed, or multiple different alphabets can be selected, with different ones of the multiple different alphabets being utilized to compress different portions of the digital data. Additionally, rather than explicitly specifying a specific selected alphabet, the header information can comprise information from which a same alphabet can be independently selected heuristically by both the compressor and the corresponding decompressor.

The generation of symbol-encoded data from digital data, as part of the compression of the digital data into a compressed digital data, can be performed with reference to multiple alternative alphabets. A selection of a specific alphabet is made based on the digital data being compressed, the compression parameters, or combinations thereof. Information indicative of the selected alphabet is encoded into one or more headers of the resulting compressed digital data. A single alphabet can be selected for all of a set of digital data being compressed, or multiple different alphabets can be selected, with different ones of the multiple different alphabets being utilized to compress different portions of the digital data. Additionally, rather than explicitly specifying a specific selected alphabet, the header information can comprise information from which a same alphabet can be independently selected heuristically by both the compressor and the corresponding decompressor.

Interleaving of variable bitrate streams for GPU implementations is described. An example of an apparatus includes one or more processors including a graphic processor, the graphics processor including a super-compression encoder pipeline to provide variable width interleaved coding; and memory for storage of data, wherein the graphics processor is to perform parallel dictionary encoding on a bitstream of symbols one of multiple workgroups, the workgroup to employ a plurality of encoders to generate a plurality of token-streams of variable lengths; create a histogram including at least tokens from the plurality of token-streams for the workgroup to generate an optimized entropy code; entropy code each of the plurality of token-streams for the workgroup into an encoded bitstream; and variably interleave the encoded bitstreams to generate an interleaved bitstream and bookkeep a size of the interleaved bitstream.

A method includes receiving an input data stream at a processor, and for each byte sequence from a plurality of byte sequences of the input data stream, a hash is generated and compared to a hash table to determine whether a match exists. If a match exists, that byte sequence is incrementally expanded to include one or more additional adjacent bytes from the input data stream, to produce multiple expanded byte sequences. Each of the expanded byte sequences is compared to the hash table to identify a maximum-length matched byte sequence from a set that includes the byte sequence and the plurality of expanded byte sequences. A representation of the maximum-length matched byte sequence is stored in the memory. If a match does not exist, a representation of that byte sequence is stored as a byte sequence literal in the memory.

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.

Systems, apparatuses, and methods related to bit string conversion are described. A memory resource and/or logic circuitry may be used in performance of bit string conversion operations. The logic circuitry can perform operations on bit strings, such as universal number and/or posit bit strings, to alter a level of precision (e.g., a dynamic range, resolution, etc.) of the bit strings. For instance, the memory resource can receive data comprising a bit string having a first quantity of bits that correspond to a first level of precision. The logic circuitry can determine that the bit string having the first quantity of bits has a particular data pattern and alter the first quantity of bits to a second quantity of bits that correspond to a second level of precision based, at least in part, on the determination that the bit string has the particular data pattern.

Technologies for switching network traffic include a network switch. The network switch includes one or more processors and communication circuitry coupled to the one or more processors. The communication circuity is capable of switching network traffic of multiple link layer protocols. Additionally, the network switch includes one or more memory devices storing instructions that, when executed, cause the network switch to receive, with the communication circuitry through an optical connection, network traffic to be forwarded, and determine a link layer protocol of the received network traffic. The instructions additionally cause the network switch to forward the network traffic as a function of the determined link layer protocol. Other embodiments are also described and claimed.

The disclosure relates to compressing strings by reducing the number of string characters that are stored. For example, a system may generate a first radix tree for a set of strings and a second radix tree for a reverse of each of the set of strings. The system may merge nodes of the first radix tree and/or second radix tree based on a tuning parameter. The system may identify, based on the first radix tree, beginning portions of at least two strings that match and identify, based on the second radix tree, ending portions of at least two strings that match. The system may use the matching beginning portions, the unique portions, and/or the matching ending portions to generate a pattern that matches the two or more strings. The system may store the two or more strings in association with the generated pattern without their matching beginning and/or ending portions.

Embodiments described herein provide a provide a fully unsupervised model for text compression. Specifically, the unsupervised model is configured to identify an optimal deletion path for each input sequence of texts (e.g., a sentence) and words from the input sequence are gradually deleted along the deletion path. To identify the optimal deletion path, the unsupervised model may adopt a pretrained bidirectional language model (BERT) to score each candidate deletion based on the average perplexity of the resulting sentence and performs a simple greedy look-ahead tree search to select the best deletion for each step.