A processing system is provided that includes a memory for storing an input bit stream and a processing logic, operatively coupled to the memory, to generate a first score based on: a first set of matching data related to a match between a first bit subsequence and a candidate bit subsequence within the input bit stream, and a first distance of the candidate bit subsequence from the first set of matching data. A second score is generated based on a second set of matching data related to a match between a second bit subsequence and the candidate bit subsequence, and a second distance of the candidate bit subsequence from the second set of matching data. A code to replace the first or second bit subsequence in an output bit stream is identified. Selection of the one of the bit subsequences to replace is based on a comparison of the scores.

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.

Techniques described herein relate to systems and methods of data storage, and more particularly to providing layering of file system functionality on an object interface. In certain embodiments, file system functionality may be layered on cloud object interfaces to provide cloud-based storage while allowing for functionality expected from a legacy applications. For instance, POSIX interfaces and semantics may be layered on cloud-based storage, while providing access to data in a manner consistent with file-based access with data organization in name hierarchies. Various embodiments also may provide for memory mapping of data so that memory map changes are reflected in persistent storage while ensuring consistency between memory map changes and writes. For example, by transforming a ZFS file system disk-based storage into ZFS cloud-based storage, the ZFS file system gains the elastic nature of cloud storage.

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.

Fast, efficient, and robust compression-based methods for detecting boundaries in arbitrary datasets, including sequences (1D datasets), are desired. The methods, each employing three simple algorithms, approximate the information distance between two adjacent sliding windows within a dataset. One of the algorithms calculates an initial ordered list of subsequences; while a second algorithm updates the ordered list of subsequences by dropping a first entry and appending a last entry rather than calculating completely new ordered lists with each iteration. Large values in the distance metric are indicative of boundary locations. A smoothed z-score or a wavelet-based algorithm may then be used to locate peaks in the distance metric, thereby identifying boundary locations. An adaptive version of the method employs a collection of window sizes and corresponding weighting functions, making it more amenable to real datasets with unknown, complex, and changing structures.

Technologies for allocating resources of managed nodes to workloads to balance multiple resource allocation objectives include an orchestrator server to receive resource allocation objective data indicative of multiple resource allocation objectives to be satisfied. The orchestrator server is additionally to determine an initial assignment of a set of workloads among the managed nodes and receive telemetry data from the managed nodes. The orchestrator server is further to determine, as a function of the telemetry data and the resource allocation objective data, an adjustment to the assignment of the workloads to increase an achievement of at least one of the resource allocation objectives without decreasing an achievement of another of the resource allocation objectives, and apply the adjustments to the assignments of the workloads among the managed nodes as the workloads are performed. Other embodiments are also described and claimed.

Methods and apparatus to parallelize data decompression are disclosed. An example method selecting initial starting positions in a compressed data bitstream; adjusting a first one of the initial starting positions to determine a first adjusted starting position by decoding the bitstream starting at a training position in the bitstream, the decoding including traversing the bitstream from the training position as though first data located at the training position is a valid token; outputting first decoded data generated by decoding a first segment of the bitstream starting from the first adjusted starting position; and merging the first decoded data with second decoded data generated by decoding a second segment of the bitstream, the decoding of the second segment starting from a second position in the bitstream and being performed in parallel with the decoding of the first segment, and the second segment preceding the first segment in the bitstream.

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 system can receive data to be written to a non-volatile memory in the distributed storage system. The received data can include a plurality of input segments. The system can assign consecutive logical block addresses (LBAs) to the plurality of input segments. The system can then compress the plurality of input segments to generate a plurality of fixed-length compressed segments, with each fixed-length compressed segment aligned with a physical block address (PBA) in a set of PBAs. The system compresses the plurality of input segments to enable an efficient use of storage capacity in the non-volatile memory. Next, the system can write the plurality of fixed-length compressed segments to a corresponding set of PBAs in the non-volatile memory. The system can then create, in a data structure, a set of entries which map the LBAs of the input segments to the set of PBAs. This data structure can be used later by the system when processing a read request including a LBA.