According to one embodiment, an interleaving unit divides a symbol string into first and second symbols. A first coding unit converts the first symbols to first codewords. A first packet generating unit generates first packets including the first codewords. A first request generating unit generates first packet requests including sizes of variable length packets. A second coding unit converts the second symbols to second codewords. A second packet generating unit generates second packets including the second codewords. A second request generating unit generates second packet requests including sizes of variable length packets. A multiplexer outputs a compressed stream including the first and second variable length packets cut out from the first and second packets.

Systems and methods for genome sequence compression and decompression are provided. The method for compression encoding of a genome sequence includes partitioning a genome sequence into a plurality of Group of Bases (GoBs) and processing each of the plurality of GoBs independently to encode the genome sequence into a bit stream. Processing each of the plurality of GoBs includes dividing each of the plurality of GOBs into a first part and a second part, the first part including an initial context part and the second part including a learning-based inference part. The processing each of the plurality of GoBs further includes encoding the first part in accordance with a Markov model, encoding the second part in accordance with a learning-based model, and encoding the encoded first part and the encoded second part into the bit stream with an arithmetic encoder. The learning-based model may include Long and Short-Term Memory (LSTM)-based neural networks.

Approaches to dictionary-based data compression are disclosed, including those in which a Zbuffer is used to identify phrases that represent uncompressed data and/or to generate decompressed data by combining a set of overlapping occluded phrases.

A memory system includes a nonvolatile memory, an interface circuit, and a controller configured to upon receipt of a plurality of write commands for storing write data in the nonvolatile memory via the interface circuit, acquire compression-ratio information about the write data associated with each write command, determine a compression ratio of each write data based on the acquired compression-ratio information, and determine an execution order of the write commands based on the determined compression ratio.

Systems and methods for fault-tolerant threshold circuits used in converting an analog input to a single-bit digital output employ N-modular redundancy of either inverting or non-inverting threshold circuits whose inputs are connected to a single input, and apply majority voting of their outputs to provide correction of transient or permanent faults in up to floor[(N−1)/2] of the individual threshold circuits. Using summation to perform analog majority voting averages the N threshold circuit outputs and provides resilience to single-event transients, but may exhibit an output characteristic having intermediate voltage levels. A digital majority voter having N inputs connected to the outputs of N threshold circuits restores well-defined logic levels and clean hysteresis for Schmitt trigger threshold circuits. A single point of failure at the digital majority voter may be eliminated using an analog majority voter to sum the outputs of three or more redundant digital majority voters.

A compression ratio (CR) adapter (CRA) for end-to-end data-driven compressive sensing (CS) reconstruction (EDCSR) frameworks is provided. EDCSR frameworks achieve state-of-the-art reconstruction performance in terms of reconstruction speed and accuracy for images and other signals. However, existing EDCSR frameworks cannot adapt to a variable CR. For applications that desire a variable CR, existing EDCSR frameworks must be trained from scratch at each CR, which is computationally costly and time-consuming. Embodiments described herein present a CRA framework that addresses the variable CR problem generally for existing and future EDCSR frameworks with no modification to given reconstruction models nor enormous additional rounds of training needed. The CRA exploits an initial reconstruction network to generate an initial estimate of reconstruction results based on a small portion of acquired image measurements. Subsequently, the CRA approximates full measurements for the main reconstruction network by complementing the sensed measurements with a re-sensed initial estimate.

Systems and methods for stream-based compression are described. One example is an encoder of a first device that receives an input stream of bytes including a first byte preceded by one or more second bytes. The encoder may determine to identify a prefix code for the first byte. The encoder may select a prefix code table using the one or more second bytes. The encoder may identify, from the selected prefix code table, the prefix code of the first byte. The encoder may generate an output stream of bytes by replacing the first byte in the input stream with the prefix code of the first byte. The encoder may transmit the output stream from the encoder of the first device to a decoder of a second device. The output stream may have a fewer number of bits than the input stream.

Systems and methods for lossless compression of tabular numeric data are provided. The system can include one or more data compression servers executing data compression system code to compress the tabular numeric data, a storage database to store the compressed tabular numeric data, and one or more data decompression servers to decompress the tabular numeric data for use. The one or more data compression servers, the storage database, and the one or more data decompression servers can communicate via a communication network. The system can receive the uncompressed tabular numeric data from one or more data generation systems, processes the uncompressed tabular numeric data with the data compression system code, and generate a compressed table of numeric information, which can be stored in the database, or later decompressed by the one or more data decompression servers.

Techniques are disclosed for identifying fixed bits of a bitstring format. One or more processors are configured to generate a first bitstring having respective first bit values that have a first satisfiability state and generate a second bitstring having respective second bit values that have a second satisfiability state. The one or more processors are configured to identify first potential free bits having respective first common values and generate a third bitstring having first potential free bits with the respective first common values and third remaining bits. The one or more processors are configured to identify second potential free bits having respective second common values and identify a fixed bit that is not included in the first potential free bits and is not included in the second potential free bits.

An apparatus and method for performing efficient lossless compression. For example, one embodiment of an apparatus comprises: first compression circuitry to identify and replace one or more repeated bit strings from an input data stream with distances to the one or more repeated bit strings, the first compression circuitry to generate a first compressed data stream comprising literal-length data identifying a first instance of each repeated bit string and distance data comprising distances from the first instance to each repeated instance of the repeated bit string; second compression circuitry to perform sorting, tree generation, and length calculations for literal-length values and distance values of the first compressed data stream, the second compression circuitry comprising: variable length code mapping circuitry to map each literal-length value and distance value to a variable length code; header generation circuitry to generate a header for a final compressed bit stream using the length calculations; and a transcoder to substitute the variable length codes in place of the literal-length and distance values to generate a compressed bit stream body, wherein the transcoder operates in parallel with the header generation circuitry; and bit stream merge circuitry to combine the header with the compressed bit stream body to generate a final lossless compressed bitstream.